Bike Share Data Web App Code - Capital One Mindsumo Challenge By: Jack Lunceford Enjoy! P.S. Thank you so much for the opportunity to continue in the selection process! I greatly appreciate it! side note-some requirements may be out of order-my apologies!

In [ ]:
import pandas as pd
df = pd.read_csv("metro-bike-share-trip-data.csv")
df
In [193]:
list = []
list.append(pd.value_counts(df['Starting Station ID']))
print list
[3069.0    5138
3030.0    5059
3005.0    4883
3064.0    4661
3031.0    4629
3014.0    4571
3042.0    4015
3082.0    3908
3022.0    3893
3067.0    3797
3035.0    3406
3038.0    3306
3055.0    3270
3068.0    3252
3049.0    3154
3034.0    3037
3048.0    3005
3063.0    2949
3007.0    2785
3006.0    2708
3027.0    2557
3032.0    2466
3074.0    2341
3062.0    2325
3052.0    2253
3047.0    2230
3008.0    2156
3075.0    2125
3051.0    2062
3023.0    1980
          ... 
3056.0    1461
3066.0    1425
3046.0    1348
3011.0    1257
3021.0    1254
3018.0    1211
3028.0    1179
3037.0    1174
3036.0    1153
3040.0    1023
3065.0     992
3078.0     879
3054.0     865
3077.0     802
3059.0     742
3033.0     709
3079.0     693
3025.0     626
3081.0     593
3020.0     528
3010.0     427
3060.0     383
3057.0     380
3080.0     191
3045.0     187
3039.0     115
4108.0     108
3009.0      56
3000.0      29
3053.0      13
Name: Starting Station ID, Length: 67, dtype: int64]

From above, we can see that the pd.value_counts() function outputs the frequency, or amount of appearance times within the list, for each Starting Station ID. The output is in descending order, with the most common Start Station at the top-3069.0.

In [191]:
list2 = []
list2.append(pd.value_counts(df['Ending Station ID']))
print list2
[3005.0    6262
3031.0    5517
3014.0    5385
3042.0    5293
3069.0    5072
3082.0    4703
3064.0    4605
3022.0    4337
3030.0    4224
3063.0    3763
3035.0    3513
3067.0    3481
3038.0    3194
3048.0    3156
3034.0    3032
3006.0    2826
3032.0    2778
3023.0    2495
3049.0    2489
3055.0    2460
3074.0    2361
3075.0    2276
3008.0    2242
3062.0    2204
3019.0    2175
3047.0    1994
3007.0    1993
3076.0    1960
3058.0    1944
3051.0    1939
          ... 
3036.0    1424
3018.0    1402
3029.0    1399
3026.0    1212
3066.0    1203
3046.0    1134
3065.0    1016
3068.0     983
3000.0     955
3078.0     883
3054.0     840
3077.0     811
3033.0     778
3024.0     760
3040.0     737
3059.0     722
3079.0     717
3025.0     713
3081.0     644
3020.0     604
3028.0     521
3010.0     412
3057.0     399
3060.0     389
3045.0     319
3080.0     178
4108.0     155
3039.0     115
3009.0      68
3053.0      12
Name: Ending Station ID, Length: 67, dtype: int64]

Same thing here, but this time, the most common Ending Station is 3005.0.

In [42]:
passholder_type_list=[]
for row in df['Passholder Type']:
    passholder_type_list.append(row)
print passholder_type_list
['Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly 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'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 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'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Monthly Pass', 'Flex Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Flex Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Monthly Pass', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up', 'Walk-up']
In [43]:
pd.value_counts(df['Passholder Type'])
Out[43]:
Monthly Pass    81304
Walk-up         41224
Flex Pass        9517
Staff Annual      382
Name: Passholder Type, dtype: int64
In [45]:
passholder_type_list.count('Monthly Pass')+passholder_type_list.count('Flex Pass')+passholder_type_list.count('Staff Annual')
Out[45]:
91203

The above cell tells us that the amount of riders that include bike sharing as a regular part of their commute is 91203.

In [47]:
startingLongitudes=[]
for row in df['Starting Station Longitude']:
    startingLongitudes.append(row)
print startingLongitudes
[-118.23721, -118.23721, -118.24156, -118.24156, -118.25588, -118.23703, -118.23308999999999, -118.25384, -118.25243999999999, -118.25243999999999, -118.25243999999999, -118.25283, -118.23881000000002, -118.26013999999999, -118.23648999999999, -118.25243999999999, -118.25667, -118.26013999999999, -118.23721, -118.23128, -118.26013999999999, -118.25283, -118.26338, -118.25283, -118.24156, -118.25905, -118.25905, -118.26013999999999, -118.2664, -118.23128, -118.26636, -118.26636, -118.23721, -118.23616000000001, -118.23128, -118.24156, -118.23721, -118.2558, -118.24353, -118.2558, -118.26338, -118.25243999999999, -118.23308999999999, -118.24353, -118.24353, -118.23308999999999, -118.24353, -118.23128, -118.24353, -118.25667, -118.25283, -118.23616000000001, -118.23616000000001, -118.25283, -118.25352, -118.24353, -118.26086000000001, -118.24353, -118.24353, -118.25667, -118.25667, -118.2558, -118.23648999999999, -118.23721, -118.24353, -118.25158, -118.26013999999999, -118.25667, 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-118.260139, -118.248253, -118.250183, -118.250183, -118.254593, -118.24716200000002, -118.25698100000001, -118.238808, -118.246094, -118.246094, -118.23741100000001, -118.255798, -118.25095400000001, -118.25769, -118.246094, -118.235352, -118.235352, -118.25698100000001, -118.23741100000001, -118.252831, -118.233093, -118.23741100000001, -118.236488, -118.24353, -118.233093, -118.233093, -118.25904799999999, -118.236488, -118.260948, -118.23317, -118.240967, -118.25698100000001, -118.25244099999999, -118.238808, -118.240967, -118.23741100000001, -118.23741100000001, -118.261169, -118.238937, -118.23721299999998, -118.238937, -118.247948, -118.26455700000001, -118.248253, -118.254593, -118.248352, -118.26273300000001, -118.26273300000001, -118.252831, -118.25095400000001, -118.252831, -118.246094, -118.248253, -118.25904799999999, -118.238937, -118.26455700000001, -118.25904799999999, -118.24156200000002, -118.233093, -118.238937, -118.23741100000001, -118.23741100000001, -118.260948, -118.26455700000001, -118.25095400000001, -118.25095400000001, -118.248253, -118.25244099999999, -118.238327, -118.24353, -118.25095400000001, -118.231277, -118.235352, -118.23721299999998, -118.26273300000001, -118.247948, -118.240967, -118.26338200000001, -118.247948, -118.233093, -118.25904799999999, -118.25666799999999, -118.25666799999999, -118.25904799999999, -118.260948, -118.23741100000001, -118.23741100000001, -118.23741100000001, -118.255798, -118.24716200000002, -118.26273300000001, -118.23741100000001, -118.26273300000001, -118.26273300000001, -118.23741100000001, -118.26273300000001, -118.23741100000001, -118.26273300000001, -118.23741100000001, -118.243172, -118.25244099999999, -118.243172, -118.266403, -118.253593, -118.253593, -118.240967, -118.23721299999998, -118.23741100000001, -118.240967, -118.253593, -118.24353, -118.233093, -118.233093, -118.23741100000001, -118.260948, -118.25244099999999, -118.25244099999999, -118.233093, -118.235352, -118.25618700000001, -118.231277, -118.23741100000001, -118.23741100000001, -118.26273300000001, -118.25095400000001, -118.25095400000001, -118.25095400000001, -118.25095400000001, -118.25095400000001, -118.25666799999999, -118.251579, -118.26273300000001, -118.251579, -118.23741100000001, -118.246094, -118.23721299999998, -118.25698100000001, -118.27081299999999, -118.23721299999998, -118.268082, -118.23741100000001, -118.23741100000001, -118.243172, -118.25698100000001, -118.24716200000002, -118.24716200000002, -118.260857, -118.248253, -118.248253, -118.25244099999999, -118.251579, -118.251579, -118.24353, -118.251579, -118.251579, -118.251579, -118.23741100000001, -118.23741100000001, -118.238937]
In [48]:
startingLatitudes=[]
for row in df['Starting Station Latitude']:
    startingLatitudes.append(row)
print startingLatitudes
[34.0566101, 34.0566101, 34.0528984, 34.0528984, 34.0498886, 34.0456085, 34.0460701, 34.040599799999995, 34.0447006, 34.0447006, 34.0447006, 34.0491982, 34.0493011, 34.0437317, 34.0392189, 34.0447006, 34.045539899999994, 34.0437317, 34.0566101, 34.0348015, 34.0437317, 34.0491982, 34.0420609, 34.0491982, 34.0528984, 34.0485497, 34.0485497, 34.0437317, 34.0399818, 34.0348015, 34.0535698, 34.0535698, 34.0566101, 34.0633888, 34.0348015, 34.0528984, 34.0566101, 34.040988899999995, 34.0519409, 34.040988899999995, 34.0420609, 34.0447006, 34.0460701, 34.0519409, 34.0519409, 34.0460701, 34.0519409, 34.0348015, 34.0519409, 34.045539899999994, 34.0491982, 34.0633888, 34.0633888, 34.0491982, 34.045421600000005, 34.0519409, 34.0386086, 34.0519409, 34.0519409, 34.045539899999994, 34.045539899999994, 34.040988899999995, 34.0392189, 34.0566101, 34.0519409, 34.0441589, 34.0437317, 34.045539899999994, 34.0605583, 34.053199799999994, 34.0566101, 34.0437317, 34.0437317, 34.0399818, 34.040599799999995, 34.0504799, 34.0519409, 34.045539899999994, 34.0399818, 34.0437317, 34.0447006, 34.051101700000004, 34.0386086, 34.0605583, 34.0528984, 34.040599799999995, 34.0386086, 34.0605583, 34.0519409, 34.0566101, 34.0399818, 34.056968700000006, 34.0519409, 34.0566101, 34.0491982, 34.0485497, 34.0421104, 34.053199799999994, 34.0519409, 34.0485497, 34.051101700000004, 34.0420609, 34.0535698, 34.0535698, 34.0528984, 34.0498886, 34.0535698, 34.0528984, 34.045181299999996, 34.0633888, 34.0420609, 34.0633888, 34.0485497, 34.0566101, 34.0485497, 34.0310516, 34.0386086, 34.0566101, 34.0456085, 34.0491982, 34.0420609, 34.0493011, 34.0485497, 34.0493011, 34.0493011, 34.0633888, 34.0310516, 34.0528984, 34.045181299999996, 34.0519409, 34.056968700000006, 34.0456085, 34.0456085, 34.0528984, 34.0566101, 34.0498886, 34.0441589, 34.056968700000006, 34.0484009, 34.0493011, 34.0485497, 34.045181299999996, 34.045539899999994, 34.045181299999996, 34.051101700000004, 34.051101700000004, 34.0460701, 34.051101700000004, 34.0491982, 34.045421600000005, 34.0447006, 34.0437317, 34.0437317, 34.0519409, 34.0519409, 34.0456085, 34.0460701, 34.047748600000006, 34.047748600000006, 34.0484009, 34.0420609, 34.056968700000006, 34.0456085, 34.0566101, 34.045539899999994, 34.0484009, 34.0420609, 34.0420609, 34.0493011, 34.0519409, 34.0566101, 34.0441589, 34.0493011, 34.0633888, 34.0493011, 34.0358009, 34.028511, 34.045421600000005, 34.0485497, 34.0456085, 34.0456085, 34.0498886, 34.034210200000004, 34.0456085, 34.0456085, 34.0456085, 34.0456085, 34.0348015, 34.0348015, 34.040988899999995, 34.0566101, 34.0468216, 34.0484009, 34.045181299999996, 34.045181299999996, 34.0485497, 34.0421104, 34.0421104, 34.0468216, 34.056968700000006, 34.0456085, 34.0460701, 34.0420609, 34.056968700000006, 34.0437317, 34.0421104, 34.0485497, 34.0491982, 34.0493011, 34.0566101, 34.047748600000006, 34.0400391, 34.0447006, 34.0441589, 34.0447006, 34.0633888, 34.0566101, 34.0468216, 34.0566101, 34.0519409, 34.0508804, 34.0420609, 34.03918839999999, 34.028511, 34.0441589, 34.0493011, 34.0348015, 34.0358009, 34.0501404, 34.028511, 34.0399818, 34.028511, 34.0485497, 34.0519409, 34.0468216, 0.0, 34.034210200000004, 34.03918839999999, 34.03918839999999, 34.051101700000004, 34.0348816, 34.0493011, 34.0566101, 34.046611799999994, 34.0386086, 34.0468216, 34.0484009, 34.0358009, 34.0633888, 34.0437317, 34.03746029999999, 34.0528984, 34.0519409, 34.0519409, 34.0519409, 34.0519409, 34.0508804, 34.0498886, 34.0566101, 34.045539899999994, 34.0566101, 34.0528984, 34.0519409, 34.0519409, 34.053199799999994, 34.0504799, 34.0566101, 34.0566101, 34.0386086, 34.040599799999995, 34.0605583, 34.0605583, 34.0493011, 34.0519409, 34.045539899999994, 34.045539899999994, 34.0460701, 34.0528984, 34.0508804, 34.045539899999994, 34.0519409, 34.047748600000006, 34.048851, 34.0441589, 34.0456085, 34.0456085, 34.0528984, 34.0605583, 34.045421600000005, 34.0528984, 34.0519409, 34.045539899999994, 34.045539899999994, 34.0460701, 34.03918839999999, 34.0460701, 34.0485497, 34.0485497, 34.046611799999994, 34.0493011, 34.0491982, 34.0484009, 34.056968700000006, 34.0583191, 34.0583191, 34.0493011, 34.0456085, 34.045421600000005, 34.040599799999995, 34.03918839999999, 34.0421104, 34.0421104, 34.0493011, 34.0441589, 34.03746029999999, 34.0491982, 34.0633888, 34.0519409, 34.0420609, 34.0535698, 34.0605583, 34.03918839999999, 34.0605583, 34.0460701, 34.0485497, 34.0310516, 34.053199799999994, 34.0519409, 34.047748600000006, 34.0386086, 34.0468216, 34.045181299999996, 34.0566101, 34.0566101, 34.0508804, 34.0420609, 34.0484009, 34.0493011, 34.0566101, 34.047748600000006, 34.0566101, 34.0509109, 34.0583191, 34.0583191, 34.0420609, 34.0504799, 34.0504799, 34.0491982, 34.047748600000006, 34.0508804, 34.051101700000004, 34.0583191, 34.0508804, 34.053199799999994, 34.0566101, 34.0484009, 34.045539899999994, 34.0348816, 34.0441589, 34.0441589, 34.0583191, 34.0386086, 34.0421104, 34.0310516, 34.0484009, 34.0358009, 34.045539899999994, 34.0498886, 34.0484009, 34.0484009, 34.0498886, 34.03918839999999, 34.051101700000004, 34.040599799999995, 34.0484009, 34.040599799999995, 34.0484009, 34.0535698, 34.0468216, 34.0484009, 34.0484009, 34.0519409, 34.0501404, 34.0605583, 34.0491982, 34.0508804, 34.0498886, 34.056968700000006, 34.0519409, 34.0485497, 34.03918839999999, 34.0485497, 34.0485497, 34.0421104, 34.0400391, 34.045539899999994, 34.051101700000004, 34.0392189, 34.0420609, 34.0460701, 34.0468216, 34.0484009, 34.0583191, 34.0491982, 34.0328598, 34.0528984, 34.0460701, 34.0441704, 34.0400391, 34.0504799, 34.0356789, 34.0468216, 34.0485497, 34.045539899999994, 34.045539899999994, 34.0456085, 34.045181299999996, 34.03918839999999, 34.0493011, 34.0493011, 34.0447006, 34.0519409, 34.0420609, 34.0535698, 34.0535698, 34.0420609, 34.056968700000006, 34.0485497, 34.0421104, 34.053199799999994, 34.0421104, 34.0504799, 34.0566101, 34.0460701, 34.0566101, 34.0441589, 34.03918839999999, 34.045421600000005, 34.045539899999994, 34.0566101, 34.0566101, 34.0528984, 34.045539899999994, 34.0566101, 34.0528984, 34.0485497, 34.0633888, 34.0498886, 34.0605583, 34.0519409, 34.0499802, 34.0499802, 34.0485497, 34.0392189, 34.0485497, 34.0485497, 34.0508804, 34.0348015, 34.0583191, 34.045539899999994, 34.0441704, 34.0447006, 34.0447006, 34.0421104, 34.0421104, 34.045181299999996, 34.0460701, 34.0460701, 34.0566101, 34.0485497, 34.051101700000004, 34.0493011, 34.051101700000004, 34.051101700000004, 34.0583191, 34.045539899999994, 34.0456085, 34.0437317, 34.0358009, 34.0358009, 34.0519409, 34.0519409, 34.03918839999999, 34.0447006, 34.0605583, 34.0605583, 34.047748600000006, 34.0358009, 34.0358009, 34.063179, 34.0485497, 34.0447006, 34.0447006, 34.0468216, 34.0399818, 34.0484009, 34.051101700000004, 34.045181299999996, 34.045181299999996, 34.0485497, 34.0484009, 34.0421104, 34.0605583, 34.0605583, 34.0484009, 34.0468216, 34.0484009, 34.0508804, 34.0468216, 34.0399818, 34.0399818, 34.0528984, 34.0528984, 34.045539899999994, 34.053199799999994, 34.047748600000006, 34.047748600000006, 34.045181299999996, 34.0485497, 34.0485497, 34.047748600000006, 34.047748600000006, 34.0358009, 34.0358009, 34.0566101, 34.0566101, 34.0509109, 34.0509109, 34.0441704, 34.045539899999994, 34.0399818, 34.0491982, 34.0491982, 34.045539899999994, 34.045539899999994, 34.0421104, 34.0528984, 34.03746029999999, 34.03746029999999, 34.0456085, 34.0468216, 34.0468216, 34.0437317, 34.0437317, 34.0348015, 34.0491982, 34.0491982, 34.063179, 34.045181299999996, 34.0441589, 34.03746029999999, 34.0356789, 34.045539899999994, 34.0468216, 34.0456085, 34.0358009, 34.047748600000006, 34.0400391, 34.0509109, 34.0356789, 34.045539899999994, 34.0421104, 34.0421104, 34.056968700000006, 34.056968700000006, 34.0456085, 34.0498886, 34.0348015, 34.0348015, 34.0348015, 34.0460701, 34.0420609, 34.0420609, 34.0441704, 34.0485497, 34.0642815, 34.0420609, 34.0456085, 34.0456085, 34.045181299999996, 34.053199799999994, 34.0447006, 34.0447006, 34.0399818, 34.0441589, 34.0356789, 34.0447006, 34.0468216, 34.0508804, 34.0447006, 34.0421104, 34.0421104, 34.045539899999994, 34.056968700000006, 34.0508804, 34.0441704, 34.0447006, 34.0447006, 34.0441704, 34.0356789, 34.0468216, 34.048851, 34.0460701, 34.045181299999996, 34.0509109, 34.0421104, 34.0421104, 34.0493011, 34.0519409, 34.0484009, 34.0484009, 34.0519409, 34.045181299999996, 34.0498886, 34.0519409, 34.0456085, 34.0642815, 34.0441589, 34.056968700000006, 34.040988899999995, 34.0460701, 34.0348015, 34.0447006, 34.046611799999994, 34.0633888, 34.0456085, 34.0456085, 34.0447006, 34.045421600000005, 34.03918839999999, 34.0484009, 34.0447006, 34.048851, 34.0456085, 34.0508804, 34.048851, 34.0468216, 34.0400391, 34.0400391, 34.053199799999994, 34.0633888, 34.056968700000006, 34.0386086, 34.045539899999994, 34.0348816, 34.0348816, 34.0420609, 34.0441704, 34.0421104, 34.0421104, 34.051101700000004, 34.0447006, 34.045181299999996, 34.0485497, 34.0420609, 34.0504799, 34.053199799999994, 34.047748600000006, 34.040599799999995, 34.0456085, 34.0447006, 34.0508804, 34.0447006, 34.0508804, 34.051101700000004, 34.045181299999996, 34.03987120000001, 34.0485497, 34.0508804, 34.0508804, 34.0441589, 34.056968700000006, 34.0509109, 34.0456085, 34.0535698, 34.0501404, 34.0421104, 34.0441589, 34.045539899999994, 34.0508804, 34.0498886, 34.0484009, 34.0535698, 34.0535698, 34.0605583, 34.0508804, 34.0456085, 34.0508804, 34.0456085, 34.0456085, 34.047748600000006, 34.0566101, 34.0447006, 34.045539899999994, 34.0519409, 34.0399818, 34.0447006, 34.0447006, 34.045181299999996, 34.0421104, 34.0421104, 34.0310516, 34.0583191, 34.0485497, 34.0485497, 34.0485497, 34.0392189, 34.0642815, 34.0493011, 34.0493011, 34.0642815, 34.0491982, 34.0485497, 34.0566101, 34.0519409, 34.0392189, 34.0491982, 34.0508804, 34.053199799999994, 34.053199799999994, 34.0399818, 34.0437317, 34.0437317, 34.0493011, 34.0447006, 34.0498886, 34.0498886, 34.0493011, 34.0447006, 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34.0532, 34.04681, 34.05661, 34.039982, 34.04998, 34.046822, 34.034882, 34.056969, 34.056969, 34.046611999999996, 34.046822, 34.050911, 34.051102, 34.048401, 34.044159, 34.046822, 34.041129999999995, 34.041129999999995, 34.04998, 34.04855, 34.039219, 34.04652, 34.042061, 34.052898, 34.052898, 34.038609, 34.05661, 34.038609, 34.038609, 34.051102, 34.038609, 34.038609, 34.038609, 34.038609, 34.056969, 34.04607, 34.049198, 34.053020000000004, 34.04417, 34.05048, 34.045181, 34.050911, 34.048401, 34.04855, 34.051102, 34.045181, 34.05088, 34.050911, 34.05088, 34.04607, 34.05088, 34.046611999999996, 34.046611999999996, 34.046611999999996, 34.046611999999996, 34.046611999999996, 34.04607, 34.038609, 34.046611999999996, 34.039982, 34.043732, 34.051102, 34.049198, 34.049198, 34.037459999999996, 34.037459999999996, 34.04417, 34.0532, 34.04211, 34.045181, 34.04998, 34.047748999999996, 34.04652, 34.04554, 34.049301, 34.05357, 34.045181, 34.0532, 34.046611999999996, 34.0532, 34.04211, 34.04211, 34.04211, 34.038609, 34.050911, 34.038609, 34.046611999999996, 34.04998, 34.049198, 34.05048, 34.035801, 34.04855, 34.04554, 34.051941, 34.05088, 34.039219, 34.063179, 34.051941, 34.05048, 34.05088, 34.051941, 34.04681, 34.063179, 34.037459999999996, 34.05088, 34.045181, 34.044701, 34.04681, 34.04681, 34.058319, 34.046822, 34.0406, 34.0532, 34.04998, 34.063179, 34.04998, 34.041129999999995, 34.04607, 34.04607, 34.039982, 34.044159, 34.039982, 34.05661, 34.04417, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.04681, 34.0532, 34.049198, 34.046822, 34.04681, 34.046822, 34.041129999999995, 34.04855, 34.044701, 34.049889, 34.046822, 34.051941, 34.05048, 34.037459999999996, 34.0406, 34.0406, 34.051941, 34.041129999999995, 34.041129999999995, 34.05088, 34.05088, 34.0406, 34.05661, 34.044701, 34.04607, 34.034801, 34.04607, 34.05661, 34.04607, 34.045181, 34.044159, 34.04855, 34.05088, 34.05357, 34.041691, 34.05088, 34.04417, 34.035801, 34.035801, 34.039982, 34.041691, 34.035801, 34.04998, 34.039219, 34.048401, 34.04681, 34.05357, 34.05357, 34.05661, 34.05661, 34.041691, 34.063389, 34.045421999999995, 34.052898, 34.037459999999996, 34.049889, 34.048401, 34.04855, 34.039982, 34.044701, 34.056969, 34.04998, 34.041691, 34.04417, 34.051941, 34.051941, 34.051941, 34.051941, 34.046611999999996, 34.037459999999996, 34.041691, 34.041691, 34.063179, 34.044159, 34.049301, 34.044159, 34.045421999999995, 34.049301, 34.049301, 34.04417, 34.049301, 34.0406, 34.034209999999995, 34.049301, 34.0406, 34.050911, 34.048401, 34.05661, 34.064281, 34.0532, 34.039219, 34.044159, 34.05772, 34.045421999999995, 34.04652, 34.0406, 34.051941, 34.048851, 34.050911, 34.05048, 34.05014, 34.04607, 34.046822, 34.04211, 34.039982, 34.045421999999995, 34.041129999999995, 34.051102, 34.05661, 34.05772, 34.045421999999995, 34.037048, 34.041691, 34.051941, 34.056969, 34.056969, 34.041691, 34.041129999999995, 34.04417, 34.044159, 34.044701, 34.042061, 34.051102, 34.060558, 34.060558, 34.050911, 34.050911, 34.060558, 34.0532, 34.037048, 34.035801, 34.050911, 34.05088, 34.047748999999996, 34.045181, 34.043732, 34.05088, 34.031890999999995, 34.031890999999995, 34.05048, 34.04998, 34.04681, 34.049301, 34.058319, 34.058319, 34.04652, 34.040989, 34.0532, 34.034882, 34.058319, 34.041691, 34.041691, 34.04681, 34.04652, 34.049198, 34.04607, 34.04652, 34.039219, 34.051941, 34.04607, 34.04607, 34.04855, 34.039219, 34.048401, 34.035801, 34.050911, 34.04681, 34.044701, 34.049301, 34.050911, 34.04652, 34.04652, 34.04417, 34.064281, 34.05661, 34.064281, 34.053020000000004, 34.051102, 34.05088, 34.05048, 34.046822, 34.046611999999996, 34.046611999999996, 34.049198, 34.0532, 34.049198, 34.058319, 34.05088, 34.04855, 34.064281, 34.051102, 34.04855, 34.052898, 34.04607, 34.064281, 34.04652, 34.04652, 34.048401, 34.051102, 34.0532, 34.0532, 34.05088, 34.044701, 34.060558, 34.051941, 34.0532, 34.034801, 34.041691, 34.05661, 34.046611999999996, 34.053020000000004, 34.050911, 34.042061, 34.053020000000004, 34.04607, 34.04855, 34.04554, 34.04554, 34.04855, 34.048401, 34.04652, 34.04652, 34.04652, 34.040989, 34.04998, 34.046611999999996, 34.04652, 34.046611999999996, 34.046611999999996, 34.04652, 34.046611999999996, 34.04652, 34.046611999999996, 34.04652, 34.047748999999996, 34.044701, 34.047748999999996, 34.039982, 34.056969, 34.056969, 34.050911, 34.05661, 34.04652, 34.050911, 34.056969, 34.051941, 34.04607, 34.04607, 34.04652, 34.048401, 34.044701, 34.044701, 34.04607, 34.041691, 34.04211, 34.034801, 34.04652, 34.04652, 34.046611999999996, 34.0532, 34.0532, 34.0532, 34.0532, 34.0532, 34.04554, 34.044159, 34.046611999999996, 34.044159, 34.04652, 34.058319, 34.05661, 34.04681, 34.035678999999995, 34.05661, 34.03286, 34.04652, 34.04652, 34.047748999999996, 34.04681, 34.04998, 34.04998, 34.038609, 34.05088, 34.05088, 34.044701, 34.044159, 34.044159, 34.051941, 34.044159, 34.044159, 34.044159, 34.04652, 34.04652, 34.064281]
In [49]:
endingLatitudes=[]
for row in df['Ending Station Latitude']:
    endingLatitudes.append(row)
print endingLatitudes
[34.0566101, 34.0566101, 34.0528984, 34.0528984, 34.0498886, 34.0392189, 34.0566101, 34.0485497, 34.0447006, 34.0642815, 34.0399818, 34.0485497, 34.0519409, 34.0437317, 34.0519409, 34.040599799999995, 34.040988899999995, 34.0504799, 34.0528984, 34.0491982, 34.053199799999994, 34.0566101, 34.0386086, 34.0566101, 34.040988899999995, 34.051101700000004, 34.0456085, 34.053199799999994, 34.0519409, 34.0348015, 34.045539899999994, 34.045539899999994, 34.0566101, 34.0528984, 34.0493011, 34.0498886, 34.0566101, 34.03918839999999, 34.0519409, 34.0519409, 34.0400391, 34.0605583, 34.0484009, 34.0566101, 34.0528984, 34.0583191, 34.0566101, 34.0460701, 34.0437317, 34.0441589, 34.040988899999995, 34.0358009, 34.0358009, 34.0605583, 34.045421600000005, 34.0566101, 34.0386086, 34.0605583, 34.0605583, 34.051101700000004, 34.051101700000004, 34.045539899999994, 34.0566101, 34.0519409, 34.0528984, 34.0468216, 34.0468216, 34.0399818, 34.0447006, 34.0566101, 34.0605583, 34.0386086, 34.0386086, 34.0437317, 34.0437317, 34.0399818, 34.0493011, 34.0566101, 34.0491982, 34.0421104, 34.0441589, 34.0504799, 34.0491982, 34.0605583, 34.0566101, 34.0498886, 34.0491982, 34.0605583, 34.045181299999996, 34.0528984, 34.0437317, 34.0399818, 34.0493011, 34.0528984, 34.0485497, 34.0535698, 34.0485497, 34.0566101, 34.0485497, 34.0519409, 34.056968700000006, 34.0447006, 34.0493011, 34.0493011, 34.0528984, 34.045539899999994, 34.0485497, 34.0421104, 34.0605583, 34.0633888, 34.0528984, 34.045539899999994, 34.0528984, 34.045539899999994, 34.047748600000006, 34.0310516, 34.047748600000006, 34.045181299999996, 34.045539899999994, 34.0642815, 34.045421600000005, 34.056968700000006, 34.0493011, 34.0468216, 34.0519409, 34.0642815, 34.0310516, 34.0447006, 34.0493011, 34.0456085, 34.040988899999995, 34.051101700000004, 34.051101700000004, 34.0566101, 34.0566101, 34.0519409, 34.045539899999994, 34.045539899999994, 34.0437317, 34.0519409, 34.056968700000006, 34.0456085, 34.0460701, 34.0456085, 34.0484009, 34.0484009, 34.0358009, 34.0484009, 34.0437317, 34.0633888, 34.0392189, 34.0437317, 34.0437317, 34.0420609, 34.0420609, 34.0460701, 34.0456085, 34.0456085, 34.0456085, 34.051101700000004, 34.045539899999994, 34.0484009, 34.0420609, 34.047748600000006, 34.0420609, 34.045539899999994, 34.0456085, 34.0456085, 34.0493011, 34.0485497, 34.045539899999994, 34.0447006, 34.0348015, 34.0633888, 34.0348015, 34.0348015, 34.034210200000004, 34.0485497, 34.045421600000005, 34.0447006, 34.0447006, 34.056968700000006, 34.028511, 34.045181299999996, 34.045181299999996, 34.0399818, 34.0399818, 34.0493011, 34.0493011, 34.056968700000006, 34.0485497, 34.0468216, 34.0447006, 34.047748600000006, 34.047748600000006, 34.0535698, 34.0468216, 34.0420609, 34.0566101, 34.0519409, 34.0456085, 34.0421104, 34.03746029999999, 34.051101700000004, 34.0491982, 34.0484009, 34.0528984, 34.0501404, 34.0484009, 34.0519409, 34.0485497, 34.0498886, 34.046611799999994, 34.0519409, 34.0519409, 34.0491982, 34.0358009, 34.0519409, 34.053199799999994, 34.0456085, 34.0519409, 34.0485497, 34.0493011, 34.028511, 34.028511, 34.0504799, 34.0421104, 34.0460701, 34.03918839999999, 34.034210200000004, 34.0504799, 34.0441589, 34.0519409, 34.0519409, 34.040599799999995, 0.0, 34.0386086, 34.0528984, 34.0501404, 34.0484009, 34.0348816, 34.0493011, 34.0485497, 34.045539899999994, 34.028511, 34.0519409, 34.0508804, 34.0566101, 34.045421600000005, 34.046611799999994, 34.0420609, 34.0519409, 34.0485497, 34.0484009, 34.0485497, 34.0508804, 34.0605583, 34.056968700000006, 34.0519409, 34.045181299999996, 34.0605583, 34.0566101, 34.0456085, 34.0456085, 34.0583191, 34.03918839999999, 34.0460701, 34.0460701, 34.0386086, 34.0468216, 34.0566101, 34.051101700000004, 34.0519409, 34.0468216, 34.0566101, 34.0566101, 34.0358009, 34.0508804, 34.0519409, 34.0633888, 34.045421600000005, 34.047748600000006, 34.048851, 34.0491982, 34.0519409, 34.0519409, 34.0519409, 34.0491982, 34.0456085, 34.0528984, 34.053199799999994, 34.0566101, 34.0566101, 34.0566101, 34.03918839999999, 34.0566101, 34.0484009, 34.0484009, 34.046611799999994, 34.040599799999995, 34.040599799999995, 34.0441589, 34.0493011, 34.053199799999994, 34.0605583, 34.0566101, 34.0491982, 34.0528984, 34.047748600000006, 34.0504799, 34.0504799, 34.0504799, 34.053199799999994, 34.0460701, 34.045539899999994, 34.0633888, 34.0509109, 34.0468216, 34.0508804, 34.051101700000004, 34.0485497, 34.03918839999999, 34.056968700000006, 34.047748600000006, 34.048851, 34.0386086, 34.0484009, 34.0456085, 34.0437317, 34.0310516, 34.0468216, 34.0508804, 34.0583191, 34.0583191, 34.0420609, 34.0420609, 34.0447006, 34.0493011, 34.0484009, 34.0493011, 34.0441704, 34.0633888, 34.045539899999994, 34.045539899999994, 34.0605583, 34.0421104, 34.0421104, 34.046611799999994, 34.0468216, 34.0484009, 34.051101700000004, 34.0485497, 34.045181299999996, 34.0493011, 34.0528984, 34.051101700000004, 34.0504799, 34.0348816, 34.0441589, 34.0441589, 34.0498886, 34.0468216, 34.0491982, 34.045181299999996, 34.0583191, 34.0358009, 34.0358009, 34.063179, 34.0421104, 34.0421104, 34.0484009, 34.0468216, 34.056968700000006, 34.046611799999994, 34.0441589, 34.0485497, 34.0491982, 34.045539899999994, 34.045181299999996, 34.0456085, 34.0456085, 34.0493011, 34.0498886, 34.0605583, 34.0358009, 34.0605583, 34.0441704, 34.0421104, 34.0508804, 34.0447006, 34.045421600000005, 34.0447006, 34.0447006, 34.0441704, 34.0485497, 34.045539899999994, 34.0504799, 34.0493011, 34.0468216, 34.03918839999999, 34.0485497, 34.063179, 34.056968700000006, 34.0437317, 34.0441704, 34.053199799999994, 34.0491982, 34.056968700000006, 34.045421600000005, 34.0468216, 34.0356789, 34.03918839999999, 34.047748600000006, 34.0441704, 34.0441704, 34.0441589, 34.045181299999996, 34.0460701, 34.0493011, 34.0493011, 34.0421104, 34.0485497, 34.0528984, 34.0485497, 34.0485497, 34.0528984, 34.0485497, 34.0493011, 34.0441704, 34.0447006, 34.045539899999994, 34.063179, 34.0491982, 34.0392189, 34.0491982, 34.0583191, 34.0493011, 34.0400391, 34.0460701, 34.0499802, 34.0499802, 34.0566101, 34.0447006, 34.0485497, 34.0566101, 34.0399818, 34.0468216, 34.045421600000005, 34.0508804, 34.0566101, 34.0484009, 34.0484009, 34.0400391, 34.040599799999995, 34.0348015, 34.0348015, 34.045539899999994, 34.063179, 34.0583191, 34.0493011, 34.0328598, 34.0485497, 34.0485497, 34.0447006, 34.0447006, 34.0468216, 34.0460701, 34.0460701, 34.0566101, 34.0485497, 34.051101700000004, 34.0456085, 34.0519409, 34.0519409, 34.047748600000006, 34.045539899999994, 34.03918839999999, 34.046611799999994, 34.0358009, 34.0358009, 34.046611799999994, 34.046611799999994, 34.0456085, 34.0485497, 34.03918839999999, 34.03918839999999, 34.0447006, 34.045181299999996, 34.045181299999996, 34.0491982, 34.0468216, 34.0421104, 34.0421104, 34.045181299999996, 34.053199799999994, 34.0437317, 34.0484009, 34.0484009, 34.0484009, 34.0535698, 34.051101700000004, 34.0421104, 34.0528984, 34.0528984, 34.0399818, 34.0566101, 34.0399818, 34.0508804, 34.048851, 34.046611799999994, 34.046611799999994, 34.0493011, 34.0493011, 34.045539899999994, 34.0399818, 34.045539899999994, 34.045539899999994, 34.0456085, 34.0420609, 34.0420609, 34.0509109, 34.0509109, 34.0420609, 34.0420609, 34.0566101, 34.0566101, 34.0447006, 34.0447006, 34.0421104, 34.051101700000004, 34.028511, 34.045539899999994, 34.045539899999994, 34.047748600000006, 34.047748600000006, 34.0421104, 34.0456085, 34.0437317, 34.0437317, 34.0528984, 34.0421104, 34.0421104, 34.0491982, 34.0491982, 34.0485497, 34.0605583, 34.0605583, 34.03746029999999, 34.0468216, 34.045539899999994, 34.03746029999999, 34.0633888, 34.045539899999994, 34.0566101, 34.0566101, 34.0358009, 34.0491982, 34.045539899999994, 34.047748600000006, 34.0400391, 34.0498886, 34.056968700000006, 34.056968700000006, 34.03918839999999, 34.03918839999999, 34.0460701, 34.0441704, 34.0421104, 34.056968700000006, 34.056968700000006, 34.0456085, 34.0420609, 34.0420609, 34.045539899999994, 34.0485497, 34.045181299999996, 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34.048401, 34.051941, 34.050911, 34.05088, 34.05088, 34.049889, 34.049198, 34.049889, 34.051941, 34.04855, 34.050911, 34.050911, 34.050911, 34.046611999999996, 34.046611999999996, 34.046611999999996, 34.046611999999996, 34.047748999999996, 34.045181, 34.049301, 34.037459999999996, 34.045421999999995, 34.04211, 34.041129999999995, 34.039219, 34.046611999999996, 34.038609, 34.05661, 34.04652, 34.050911, 34.04607, 34.04855, 34.04855, 34.04554, 34.041129999999995, 34.041129999999995, 34.04607, 34.04607, 34.048851, 34.04607, 34.047748999999996, 34.0406, 34.049301, 34.0406, 34.046822, 34.0406, 34.04998, 34.044701, 34.041691, 34.043732, 34.04211, 34.049301, 34.043732, 34.046822, 34.04652, 34.04652, 34.048401, 34.049301, 34.04652, 34.045181, 34.041691, 34.042061, 34.056969, 34.04855, 34.04855, 34.04607, 34.04607, 34.060558, 34.05661, 34.049301, 34.05661, 34.03286, 34.037459999999996, 34.039982, 34.04211, 34.04417, 34.04681, 34.04855, 34.04998, 34.039219, 34.042061, 34.060558, 34.060558, 34.05661, 34.05661, 34.051102, 34.039982, 34.05661, 34.05661, 34.046611999999996, 34.04652, 34.064281, 34.04652, 34.034801, 34.064281, 34.049301, 34.05088, 34.049301, 34.04855, 34.049198, 34.049301, 34.04855, 34.050911, 34.05661, 34.050911, 34.050911, 34.049301, 34.04607, 34.04855, 34.049301, 34.04855, 34.04554, 34.031890999999995, 34.049301, 34.049301, 34.04652, 34.044159, 34.049889, 34.039219, 34.049301, 34.05661, 34.04681, 34.04652, 34.048851, 34.044701, 34.045421999999995, 34.05661, 34.04417, 34.037048, 34.041691, 34.049301, 34.049198, 34.05661, 34.05088, 34.046822, 34.04417, 34.049889, 34.044701, 34.04681, 34.04855, 34.04652, 34.060558, 34.050911, 34.050911, 34.04652, 34.04652, 34.037048, 34.035801, 34.049301, 34.04554, 34.048401, 34.05661, 34.05661, 34.05048, 34.0406, 34.0406, 34.045181, 34.04855, 34.047748999999996, 34.04652, 34.043732, 34.043732, 34.051941, 34.048851, 34.044159, 34.037459999999996, 34.05088, 34.049301, 34.05661, 34.050911, 34.04652, 34.04652, 34.05661, nan, 34.047748999999996, 34.050911, 34.04607, 34.04607, 34.047748999999996, 34.04607, 34.044159, 34.049301, 34.04607, 34.05357, 34.049301, 34.050911, 34.064281, 34.05661, 34.05661, 34.05088, 34.064281, 34.05661, 34.064281, 34.044701, 34.051102, 34.060558, 34.041129999999995, 34.04855, 34.05661, 34.05661, 34.048401, 34.051941, 34.048401, 34.04681, 34.04417, 34.047748999999996, 34.050911, 34.046611999999996, 34.047748999999996, 34.063389, 34.04998, 34.064281, 34.056969, 34.056969, 34.042061, 34.051102, 34.04681, 34.04681, 34.049198, 34.049301, 34.05088, 34.049301, 34.049301, 34.041691, 34.04681, 34.051102, 34.05048, 34.04652, 34.064281, 34.035678999999995, 34.04652, 34.044701, 34.045181, 34.041691, 34.04652, 34.051102, 34.042061, 34.045181, 34.045181, 34.045181, 34.046822, 34.043732, 34.046611999999996, 34.045181, 34.046611999999996, 34.046611999999996, 34.045181, 34.046611999999996, 34.045181, 34.046611999999996, 34.045181, 34.047748999999996, 34.04211, 34.044159, 34.039982, 34.042061, 34.04652, 34.050911, 34.034801, 34.049198, 34.050911, 34.048851, 34.04652, nan, 34.04607, 34.0532, 34.051102, 34.048851, 34.048851, 34.045181, 34.049301, 34.04855, 34.034801, 34.053020000000004, 34.053020000000004, 34.041691, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.041129999999995, 34.04855, 34.035801, 34.051102, 34.035801, 34.05088, 34.05661, 34.04607, 34.042061, 34.03286, 34.04607, 34.035678999999995, 34.04652, 34.04652, 34.041691, nan, 34.04681, 34.04681, 34.063389, 34.04554, 34.04554, 34.044159, 34.04211, 34.04211, 34.044159, 34.048401, 34.048401, 34.048401, 34.039219, 34.039219, 34.048851]
In [51]:
endingLongitudes=[]
for row in df['Ending Station Longitude']:
    endingLongitudes.append(row)
print endingLongitudes
[-118.23721, -118.23721, -118.24156, -118.24156, -118.25588, -118.23648999999999, -118.23721, -118.25905, -118.25243999999999, -118.23893999999999, -118.2664, -118.25905, -118.24353, -118.26013999999999, -118.24353, -118.25384, -118.2558, -118.25459, -118.24156, -118.25283, -118.25095, -118.23721, -118.26086000000001, -118.23721, -118.2558, -118.26456, -118.23703, -118.25095, -118.24353, -118.23128, -118.25667, -118.25667, -118.23721, -118.24156, -118.23881000000002, -118.25588, -118.23721, -118.23253000000001, -118.24353, -118.24353, -118.26302, -118.23833, -118.26095, -118.23721, -118.24156, -118.24609, -118.23721, -118.23308999999999, -118.26013999999999, -118.25158, -118.2558, -118.23317, -118.23317, -118.23833, -118.25352, -118.23721, -118.26086000000001, -118.23833, -118.23833, -118.26456, -118.26456, -118.25667, -118.23721, -118.24353, -118.24156, -118.24835, -118.24835, -118.2664, -118.25243999999999, -118.23721, -118.23833, -118.26086000000001, -118.26086000000001, -118.26013999999999, -118.26013999999999, -118.2664, -118.23881000000002, -118.23721, -118.25283, -118.25618999999999, -118.25158, -118.25459, -118.25283, -118.23833, -118.23721, -118.25588, -118.25283, -118.23833, -118.25023999999999, -118.24156, -118.26013999999999, -118.2664, -118.23881000000002, -118.24156, -118.25905, -118.26636, -118.25905, -118.23721, -118.25905, -118.24353, -118.25358999999999, -118.25243999999999, -118.23881000000002, -118.23881000000002, -118.24156, -118.25667, -118.25905, -118.25618999999999, -118.23833, -118.23616000000001, -118.24156, -118.25667, -118.24156, -118.25667, -118.24316999999999, -118.26709, -118.24316999999999, -118.25023999999999, -118.25667, -118.23893999999999, -118.25352, -118.25358999999999, -118.23881000000002, -118.24835, -118.24353, -118.23893999999999, -118.26709, -118.25243999999999, -118.23881000000002, -118.23703, -118.2558, -118.26456, -118.26456, -118.23721, -118.23721, -118.24353, -118.25667, -118.25667, -118.26013999999999, -118.24353, -118.25358999999999, -118.23703, -118.23308999999999, -118.23703, -118.26095, -118.26095, -118.23317, -118.26095, -118.26013999999999, -118.23616000000001, -118.23648999999999, -118.26013999999999, -118.26013999999999, -118.26338, -118.26338, -118.23308999999999, -118.23703, -118.23703, -118.23703, -118.26456, -118.25667, -118.26095, -118.26338, -118.24316999999999, -118.26338, -118.25667, -118.23703, -118.23703, -118.23881000000002, -118.25905, -118.25667, -118.25243999999999, -118.23128, -118.23616000000001, -118.23128, -118.23128, -118.25459, -118.25905, -118.25352, -118.25243999999999, -118.25243999999999, -118.25358999999999, -118.25667, -118.25023999999999, -118.25023999999999, -118.2664, -118.2664, -118.23881000000002, -118.23881000000002, -118.25358999999999, -118.25905, -118.24835, -118.25243999999999, -118.24316999999999, -118.24316999999999, -118.26636, -118.24835, -118.26338, -118.23721, -118.24353, -118.23703, -118.25618999999999, -118.26538000000001, -118.26456, -118.25283, -118.26095, -118.24156, -118.23324, -118.26095, -118.24353, -118.25905, -118.25588, -118.26273, -118.24353, -118.24353, -118.25283, -118.23317, -118.24353, -118.25095, -118.23703, -118.24353, -118.25905, -118.23881000000002, -118.25667, -118.25667, -118.25459, -118.25618999999999, -118.23308999999999, -118.23253000000001, -118.25459, -118.25459, -118.25158, -118.24353, -118.24353, -118.25384, 0.0, -118.26086000000001, -118.24156, -118.23324, -118.26095, -118.25769, -118.23881000000002, -118.25905, -118.25667, -118.25667, -118.24353, -118.24825, -118.23721, -118.25352, -118.26273, -118.26338, -118.24353, -118.25905, -118.26095, -118.25905, -118.24825, -118.23833, -118.25358999999999, -118.24353, -118.25023999999999, -118.23833, -118.23721, -118.23703, -118.23703, -118.24609, -118.23253000000001, -118.23308999999999, -118.23308999999999, -118.26086000000001, -118.24835, -118.23721, -118.26456, -118.24353, -118.24835, -118.23721, -118.23721, -118.23317, -118.24825, -118.24353, -118.23616000000001, -118.25352, -118.24316999999999, -118.24642, -118.25283, -118.24353, -118.24353, -118.24353, -118.25283, -118.23703, -118.24156, -118.25095, -118.23721, -118.23721, -118.23721, -118.23253000000001, -118.23721, -118.26095, -118.26095, -118.26273, -118.25384, -118.25384, -118.25158, -118.23881000000002, -118.25095, -118.23833, -118.23721, -118.25283, -118.24156, -118.24316999999999, -118.25459, -118.25459, -118.25459, -118.25095, -118.23308999999999, -118.25667, -118.23616000000001, -118.24096999999999, -118.24835, -118.24825, -118.26456, -118.25905, -118.23253000000001, -118.25358999999999, -118.24316999999999, -118.24642, -118.26086000000001, -118.26095, -118.23703, -118.26013999999999, -118.26709, -118.24835, -118.24825, -118.24609, -118.24609, -118.26338, -118.26338, -118.25243999999999, -118.23881000000002, -118.26095, -118.23881000000002, -118.26116999999999, -118.23616000000001, -118.25667, -118.25667, -118.23833, -118.25618999999999, -118.25618999999999, -118.26273, -118.24835, -118.26095, -118.26456, -118.25905, -118.25023999999999, -118.23881000000002, -118.24156, -118.26456, -118.25459, -118.25769, -118.25158, -118.25158, -118.25588, -118.24835, -118.25283, -118.25023999999999, -118.24609, -118.23317, -118.23317, -118.24588, -118.25618999999999, -118.25618999999999, -118.26095, -118.24835, -118.25358999999999, -118.26273, -118.25158, -118.25905, -118.25283, -118.25667, -118.25023999999999, -118.23703, -118.23703, -118.23881000000002, -118.25588, -118.23833, -118.23317, -118.23833, -118.26116999999999, -118.25618999999999, -118.24825, -118.25243999999999, -118.25352, -118.25243999999999, -118.25243999999999, -118.26116999999999, -118.25905, -118.25667, -118.25459, -118.23881000000002, -118.24835, -118.23253000000001, -118.25905, -118.24588, -118.25358999999999, -118.26013999999999, -118.26116999999999, -118.25095, -118.25283, -118.25358999999999, -118.25352, -118.24835, -118.27081000000001, -118.23253000000001, -118.24316999999999, -118.26116999999999, -118.26116999999999, -118.25158, -118.25023999999999, -118.23308999999999, -118.23881000000002, -118.23881000000002, -118.25618999999999, -118.25905, -118.24156, -118.25905, -118.25905, -118.24156, -118.25905, -118.23881000000002, -118.26116999999999, -118.25243999999999, -118.25667, -118.24588, -118.25283, -118.23648999999999, -118.25283, -118.24609, -118.23881000000002, -118.26302, -118.23308999999999, -118.24716000000001, -118.24716000000001, -118.23721, -118.25243999999999, -118.25905, -118.23721, -118.2664, -118.24835, -118.25352, -118.24825, -118.23721, -118.26095, -118.26095, -118.26302, -118.25384, -118.23128, -118.23128, -118.25667, -118.24588, -118.24609, -118.23881000000002, -118.26808, -118.25905, -118.25905, -118.25243999999999, -118.25243999999999, -118.24835, -118.23308999999999, -118.23308999999999, -118.23721, -118.25905, -118.26456, -118.23703, -118.24353, -118.24353, -118.24316999999999, -118.25667, -118.23253000000001, -118.26273, -118.23317, -118.23317, -118.26273, -118.26273, -118.23703, -118.25905, -118.23253000000001, -118.23253000000001, -118.25243999999999, -118.25023999999999, -118.25023999999999, -118.25283, -118.24835, -118.25618999999999, -118.25618999999999, -118.25023999999999, -118.25095, -118.26013999999999, -118.26095, -118.26095, -118.26095, -118.26636, -118.26456, -118.25618999999999, -118.24156, -118.24156, -118.2664, -118.23721, -118.2664, -118.24825, -118.24642, -118.26273, -118.26273, -118.23881000000002, -118.23881000000002, -118.25667, -118.2664, -118.25667, -118.25667, -118.23703, -118.26338, -118.26338, -118.24096999999999, -118.24096999999999, -118.26338, -118.26338, -118.23721, -118.23721, -118.25243999999999, -118.25243999999999, -118.25618999999999, -118.26456, -118.25667, -118.25667, -118.25667, -118.24316999999999, -118.24316999999999, -118.25618999999999, -118.23703, -118.26013999999999, -118.26013999999999, -118.24156, -118.25618999999999, -118.25618999999999, -118.25283, -118.25283, -118.25905, -118.23833, -118.23833, -118.26538000000001, -118.24835, -118.25667, -118.26538000000001, -118.23616000000001, -118.25667, -118.23721, -118.23721, -118.23317, -118.25283, -118.25667, -118.24316999999999, -118.26302, -118.25588, -118.25358999999999, -118.25358999999999, -118.23253000000001, -118.23253000000001, -118.23308999999999, -118.26116999999999, -118.25618999999999, -118.25358999999999, -118.25358999999999, -118.23703, -118.26338, -118.26338, -118.25667, -118.25905, -118.25023999999999, -118.25384, -118.25283, -118.25618999999999, -118.23703, -118.23703, -118.26116999999999, -118.26116999999999, -118.24835, -118.23616000000001, -118.24825, -118.25667, -118.25243999999999, -118.25243999999999, -118.25243999999999, -118.25243999999999, -118.25243999999999, -118.25243999999999, -118.23308999999999, -118.23721, -118.25023999999999, -118.26095, -118.26095, -118.25023999999999, -118.23253000000001, -118.23128, -118.23881000000002, -118.24609, -118.25905, -118.23881000000002, -118.26095, -118.26095, -118.23721, -118.23253000000001, -118.25618999999999, -118.25618999999999, -118.23253000000001, -118.24835, -118.25588, -118.23253000000001, -118.25352, -118.25243999999999, -118.26095, -118.24825, -118.2558, -118.23881000000002, -118.23703, -118.25243999999999, -118.25283, -118.23833, -118.24353, -118.24353, -118.24316999999999, -118.25095, -118.24353, -118.25618999999999, -118.24096999999999, -118.24825, -118.24316999999999, -118.26086000000001, -118.24825, -118.26116999999999, -118.25769, -118.25769, -118.23703, -118.24609, -118.25003999999998, -118.2558, -118.25283, -118.26338, -118.26338, -118.25283, -118.24835, -118.24825, -118.24825, -118.25459, -118.27081000000001, -118.25384, -118.23616000000001, -118.26338, -118.24353, -118.25588, -118.25243999999999, -118.25023999999999, -118.23324, -118.25588, -118.23703, -118.25588, -118.23703, -118.25667, -118.23703, -118.25358999999999, -118.24825, -118.24825, -118.24825, 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In [53]:
import geopy.distance
In [196]:
import math
distances=[]

for i in range(len(df)):
    if tripRouteCategories[i]=='Round Trip':
        print "distance traveled=0.0 (Round Trip)"
    else:
        if math.isnan(startingLatitudes[i])==True or math.isnan(startingLongitudes[i])==True or math.isnan(endingLatitudes[i])==True or math.isnan(endingLongitudes[i])==True or startingLatitudes[i]==0.0 or startingLongitudes[i]==0.0 or endingLatitudes[i]==0.0 or endingLongitudes[i]==0.0:
            print "Coordinate missing"
        else:
            firstPointCoords=(startingLatitudes[i], startingLongitudes[i])
            secondPointCoords=(endingLatitudes[i], endingLongitudes[i])
            distance=geopy.distance.vincenty(firstPointCoords, secondPointCoords).miles
            distances.append(distance)
print distances
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
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Coordinate missing
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
Coordinate missing
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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Coordinate missing
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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Coordinate missing
distance traveled=0.0 (Round Trip)
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Coordinate missing
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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Coordinate missing
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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Coordinate missing
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
distance traveled=0.0 (Round Trip)
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In [61]:
import numpy as np
print np.mean(distances)
0.7339399422069283

Above cell tells us the average distance traveled for a given ride-~0.734 miles.

In [64]:
from matplotlib import pyplot as plt
In [58]:
tripRouteCategories=[]
for i in df['Trip Route Category']:
    tripRouteCategories.append(i)
print tripRouteCategories
    
['Round Trip', 'Round Trip', 'Round Trip', 'Round Trip', 'Round Trip', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 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'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'Round Trip', 'Round Trip', 'Round Trip', 'One Way', 'One Way', 'Round Trip', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'Round Trip', 'Round Trip', 'Round Trip', 'One Way', 'Round Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One 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Trip', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way', 'One Way']
In [69]:
durations=[]
for row in df['Duration']:
    durations.append(row)
print durations
[180, 1980, 300, 10860, 420, 780, 600, 600, 2880, 960, 960, 720, 360, 120, 660, 480, 2100, 600, 420, 960, 1320, 1200, 240, 1140, 1020, 360, 32700, 6960, 2160, 120, 600, 600, 120, 540, 1320, 17160, 240, 840, 420, 540, 2700, 1320, 1500, 900, 1080, 86400, 600, 360, 1080, 3000, 480, 1020, 1020, 1080, 900, 1020, 600, 1800, 1740, 1260, 1260, 300, 1680, 540, 480, 1860, 360, 1800, 1260, 1320, 180, 480, 540, 300, 480, 960, 1320, 900, 1020, 240, 900, 660, 660, 2760, 360, 840, 840, 2280, 480, 240, 420, 1200, 180, 300, 600, 1140, 300, 660, 720, 24420, 540, 540, 960, 1020, 300, 240, 300, 720, 900, 1440, 1020, 1680, 960, 1980, 1020, 2400, 1200, 900, 960, 780, 12540, 1020, 720, 600, 1140, 10800, 1560, 660, 480, 480, 660, 1140, 1080, 300, 1620, 1020, 720, 9600, 1200, 360, 480, 840, 720, 720, 1260, 1200, 360, 240, 840, 600, 1380, 540, 480, 960, 900, 120, 120, 1440, 1380, 300, 240, 600, 960, 540, 240, 720, 1800, 1740, 7800, 660, 1140, 1440, 1500, 120, 1260, 360, 1020, 180, 4920, 840, 840, 360, 900, 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1980, 2040, 1860, 4080, 360, 960, 540, 420, 900, 900, 780, 780, 780, 420, 780, 180, 240, 660, 420, 300, 900, 480, 420, 480, 360, 240, 240, 780, 600, 300, 480, 180, 420, 840, 600, 240, 120, 660, 480, 240, 480, 360, 300, 360, 1080, 240, 840, 540, 960, 900, 480, 900, 240, 240, 660, 960, 1320, 480, 480, 600, 420, 1080, 60, 420, 300, 13500, 2760, 180, 180, 420, 180, 180, 300, 360, 420, 180, 240, 660, 540, 240, 540, 480, 420, 240, 480, 1080, 180, 480, 300, 600, 420, 540, 1320, 1320, 360, 360, 1260, 360, 300, 540, 960, 660, 480, 840, 420, 540, 600, 2940, 480, 2880, 60, 1500, 540, 60, 840, 12960, 360, 3420, 3360, 1140, 720, 2820, 2700, 2640, 3420, 600, 600, 420, 180, 1260, 1140, 600, 540, 480, 180, 480, 180, 300, 300, 900, 300, 420, 1020, 540, 180, 300, 300, 660, 480, 300, 360, 420, 420, 360, 840, 180, 540, 780, 3360, 540, 3600, 3600, 300, 2880, 600, 360, 540, 360, 1080, 3960, 3900, 540, 480, 1020, 420, 660, 300, 1440, 360, 480, 360, 240, 600, 780, 540, 600, 420, 300, 480, 480, 240, 480, 480, 3120, 1020, 2160, 240, 8640, 2340, 240, 600, 540, 480, 480, 720, 1680, 60, 660, 840, 2160, 360, 2100, 540, 840, 64380, 1440, 1800, 1740, 720, 360, 300, 1560, 240, 1020, 1020, 2460, 420, 1440, 480, 300, 1860, 720, 360, 1080, 420, 240, 720, 360, 30300, 3720, 540, 960, 480, 480, 240, 240, 780, 420, 1200, 720, 660, 240, 360, 600, 240, 540, 420, 300, 180, 240, 360, 960, 540, 1200, 300, 1080, 1200, 480, 540, 480, 1440, 540, 1200, 360, 14340, 480, 1140, 420, 660, 360, 420, 360, 480, 420, 720, 720, 480, 420, 480, 420, 720, 540, 420, 480, 240, 360, 420, 240, 420, 1920, 300, 120, 180, 300, 540, 180, 660, 240, 600, 840, 540, 1560, 1140, 300, 420, 360, 180, 300, 720, 300, 300, 300, 300, 300, 900, 300, 900, 840, 840, 420, 600, 600, 600, 180, 540, 360, 300, 480, 480, 360, 60, 420, 420, 360, 540, 240, 180, 540, 540, 840, 360, 720, 480, 360, 300, 1200, 480, 660, 540, 360, 60, 180, 540, 660, 840, 2520, 2460, 360, 1020, 660, 480, 540, 660, 540, 720, 420, 360, 360, 780, 480, 300, 1080, 1440, 1500, 1440, 120, 600, 300, 600, 480, 660, 420, 240, 420, 480, 180, 420, 600, 660, 960, 480, 300, 600, 180, 180, 6360, 1800, 1800, 900, 780, 600, 1080, 900, 240, 240, 300, 360, 180, 840, 360, 660, 660, 600, 480, 180, 420, 240, 960, 660, 420, 900, 540, 480, 420, 60, 300, 360, 15000, 360, 120, 300, 300, 660, 180, 360, 120, 300, 360, 360, 840, 240, 540, 240, 240, 420, 360, 660, 360, 480, 180, 300, 360, 600, 780, 960, 360, 660, 480, 300, 240, 840, 540, 420, 240, 240, 120, 180, 840, 780, 960, 600, 480, 540, 60, 660, 660, 360, 300, 480, 480, 480, 300, 720, 420, 780, 1020, 300, 1140, 480, 600, 660, 480, 600, 1080, 2280, 1440, 120, 60, 300, 1500, 300, 600, 360, 420, 540, 780, 720, 600, 480, 360, 780, 4980, 4920, 420, 300, 300, 540, 300, 480, 180, 1020, 420, 240, 300, 360, 8100, 360, 660, 540, 540, 780, 600, 600, 600, 600, 420, 600, 60, 480, 420, 240, 1020, 11880, 2100, 2160, 480, 480, 660, 360, 1380, 420, 1020, 660, 3840, 60, 420, 840, 1140, 1140, 600, 300, 840, 300, 60, 420, 720, 720, 720, 300, 600, 240, 540, 840, 780, 420, 360, 1020, 600, 420, 780, 180, 420, 240, 420, 1020, 600, 780, 480, 240, 900, 180, 420, 600, 600, 360, 1080, 2940, 840, 420, 600, 480, 420, 2160, 480, 540, 1140, 1320, 780, 300, 240, 300, 420, 240, 420, 420, 540, 180, 360, 720, 480, 1620, 1560, 4140, 660, 120, 1080, 900, 720, 300, 540, 420, 300, 780, 420, 840, 240, 780, 540, 4860, 4860, 13440, 960, 900, 840, 420, 660, 540, 960, 420, 2340, 1380, 180, 1200, 180, 480, 120, 600, 180, 600, 540, 180, 300, 420, 600, 540, 2760, 660, 2700, 420, 300, 1020, 1620, 660, 720, 420, 1200, 180, 420, 840, 480, 300, 300, 540, 780, 900, 540, 420, 1200, 300, 240, 420, 240, 480, 60, 360, 600, 360, 420, 420, 240, 60, 840, 420, 1320, 360, 720, 840, 600, 720, 1380, 720, 240, 1440, 480, 540, 1320, 420, 240, 1560, 1800, 1140, 600, 420, 360, 180, 1620, 240, 240, 360, 600, 540, 960, 480, 480, 60, 540, 1440, 1080, 420, 300, 240, 300, 1080, 180, 480, 180, 420, 480, 360, 300, 540, 180, 720, 900, 180, 540, 720, 1200, 360, 120, 240, 300, 600, 420, 1440, 600, 720, 660, 540, 1980, 600, 1920, 780, 600, 360, 600, 300, 780, 720, 960, 420, 780, 720, 960, 540, 660, 780, 1140, 600, 540, 1620, 1020, 420, 420, 480, 540, 360, 240, 1080, 480, 240, 540, 540, 420, 240, 540, 1320, 960, 300, 720, 420, 480, 420, 300, 240, 1860, 300, 300, 480, 420, 420, 540, 300, 540, 720, 180, 480, 300, 120, 120, 720, 840, 840, 1080, 71940, 420, 120, 180, 300, 300, 300, 300, 360, 180, 2400, 2340, 2340, 2220, 480, 540, 180, 300, 1260, 300, 420, 480, 2820, 2580, 1740, 780, 180, 420, 1260, 660, 420, 180, 120, 240, 480, 1980, 540, 240, 360, 300, 480, 720, 1380, 480, 480, 780, 360, 1080, 1080, 420, 120, 840, 300, 600, 540, 240, 540, 360, 360, 480, 240, 600, 540, 540, 480, 540, 360, 2520, 120, 600, 900, 180, 480, 240, 480, 120, 660, 540, 1080, 420, 1320, 180, 540, 540, 180, 780, 1140, 240, 480, 180, 660, 240, 300, 240, 540, 360, 540, 480, 3540, 480, 240, 600, 1080, 600, 1320, 240, 840, 240, 300, 60, 480, 1080, 600, 900, 540, 540, 840, 300, 600, 900, 960, 480, 480, 480, 60, 2220, 360, 600, 840, 300, 600, 420, 3180, 16080, 240, 600, 300, 300, 360, 240, 420, 300, 1740, 360, 600, 480, 300, 1620, 480, 300, 360, 180, 840, 420, 720, 420, 180, 360, 300, 2160, 1740, 360, 1080, 420, 420, 840, 240, 780, 660, 240, 1980, 840, 300, 1200, 360, 540, 840, 1260, 900, 1260, 240, 840, 300, 1320, 660, 720, 360, 360, 420, 960, 480, 540, 540, 480, 420, 660, 240, 900, 480, 1380, 420, 1380, 360, 240, 1140, 3540, 540, 1680, 1080, 420, 540, 1140, 780, 240, 360, 2700, 300, 480, 1140, 300, 360, 240, 480, 420, 420, 480, 180, 1140, 180, 660, 300, 480, 360, 420, 480, 11400, 960, 420, 360, 900, 360, 780, 480, 300, 360, 1620, 1620, 1560, 1380, 1560, 1740, 600, 540, 300, 240, 600, 2280, 420, 1140, 480, 840, 420, 1140, 420, 420, 240, 420, 360, 1020, 480, 240, 240, 660, 900, 300, 540, 840, 420, 480, 420, 1560, 360, 960, 840, 1860, 1800, 1320, 11040, 840, 960, 660, 360, 1560, 300, 600, 240, 7200, 1020, 300, 1380, 300, 540, 420, 180, 240, 1740, 660, 300, 300, 240, 300, 240, 420, 720, 420, 360, 1020, 180, 1020, 1020, 300, 420, 540, 540, 480, 2760, 300, 720, 540, 540, 300, 240, 240, 420, 840, 1260, 720, 50280, 300, 540, 540, 300, 420, 540, 300, 1740, 780, 600, 240, 300, 300, 1260, 480, 420, 1920, 900, 660, 300, 540, 480, 1440, 720, 360, 480, 300, 360, 240, 240, 1020, 240, 660, 720, 960, 1260, 480, 2280, 2280, 420, 660, 660, 240, 360, 720, 300, 1020, 720, 420, 780, 1080, 180, 420, 360, 660, 360, 720, 720, 300, 180, 600, 120, 120, 480, 360, 420, 360, 540, 540, 300, 480, 600, 660, 660, 540, 72600, 420, 660, 300, 2580, 2520, 420, 180, 240, 120, 1440, 1560, 1560, 3780, 3720, 1080, 480, 22800, 180, 300, 360, 240, 540, 420, 840, 480, 240, 180, 360, 480, 180, 1020, 480, 780, 720, 900, 120, 600, 360, 18180, 300, 1200, 900, 120, 840, 11100, 11400, 1140, 420, 540, 540, 360, 240, 360, 360, 240, 240, 360, 240, 600, 480, 240, 1080, 480, 420, 1020, 420, 180, 660, 240, 600, 1020, 660, 240, 660, 960, 480, 720, 360, 480, 540, 120, 9600, 420, 240, 360, 900, 360, 60, 12420, 960, 660, 3660, 3600, 660, 300, 480, 900, 420, 360, 300, 480, 420, 300, 540, 720, 300, 900, 660, 540, 720, 660, 180, 7920, 300, 1620, 780, 780, 420, 720, 540, 240, 480, 480, 1260, 1320, 420, 240, 840, 1200, 180, 180, 480, 480, 420, 60, 360, 60, 1080, 300, 1200, 660, 600, 1140, 960, 480, 420, 480, 720, 240, 660, 240, 300, 600, 1080, 1020, 840, 420, 420, 1380, 780, 1140, 660, 420, 300, 300, 360, 240, 660, 300, 300, 840, 480, 1500, 540, 540, 480, 1020, 900, 1440, 2220, 300, 480, 420, 840, 1620, 540, 300, 420, 3900, 300, 300, 300, 600, 780, 780, 120, 360, 720, 540, 600, 240, 1260, 1140, 720, 660, 240, 540, 300, 420, 900, 300, 1020, 1560, 1440, 10380, 780, 1020, 480, 3240, 3180, 1020, 960, 540, 840, 180, 300, 780, 720, 780, 780, 480, 480, 3300, 3180, 540, 480, 180, 420, 420, 540, 480, 540, 6480, 240, 180, 480, 540, 420, 360, 420, 180, 840, 420, 360, 840, 240, 180, 300, 1920, 720, 540, 720, 660, 480, 300, 900, 360, 360, 600, 1080, 300, 300, 480, 1140, 540, 1200, 360, 1080, 67440, 540, 420, 480, 300, 780, 780, 660, 660, 780, 600, 720, 720, 540, 480, 1200, 480, 13140, 480, 480, 1860, 2280, 360, 540, 2160, 360, 300, 240, 1140, 4800, 300, 240, 360, 6840, 660, 720, 420, 300, 420, 240, 1500, 1440, 240, 240, 420, 480, 480, 480, 1020, 600, 1020, 180, 360, 1140, 720, 960, 1020, 300, 420, 780, 420, 720, 720, 1260, 420, 300, 420, 480, 660, 10920, 60, 480, 540, 420, 780, 420, 1620, 60, 840, 420, 480, 780, 660, 1620, 180, 720, 480, 360, 300, 240, 1440, 960, 360, 360, 360, 300, 240, 2040, 1080, 420, 300, 180, 660, 420, 420, 600, 240, 240, 600, 720, 120, 480, 1080, 600, 420, 720, 300, 240, 420, 420, 2220, 120, 240, 1980, 1920, 1800, 540, 1020, 180, 360, 900, 1020, 3720, 4140, 1740, 300, 480, 1080, 120, 360, 420, 6060, 420, 540, 540, 480, 300, 86400, 420, 1500, 240, 240, 360, 360, 600, 480, 300, 1200, 60, 240, 120, 1500, 300, 480, 780, 720, 300, 480, 300, 360, 420, 300, 300, 3480, 900, 240, 600, 300, 780, 1140, 180, 960, 480, 180, 420, 3480, 360, 300, 600, 480, 2820, 25620, 660, 420, 480, 480, 31260, 480, 60, 360, 420, 360, 600, 480, 300, 660, 180, 480, 1020, 120, 600, 540, 660, 240, 480, 540, 180, 540, 1260, 1500, 51960, 360, 780, 120, 240, 86400, 660, 480, 1380, 240, 1140, 240, 960, 600, 300, 600, 120, 600, 1740, 3840, 600, 240, 900, 900, 1680, 1560, 11340, 1980, 1860, 1800, 1740, 300, 1020, 900, 360, 480, 1260, 2940, 86400, 300, 540, 900, 480, 300, 660, 780, 900, 900, 1140, 660, 840, 240, 600, 420, 360, 300, 2700, 300, 720, 540, 1740, 1680, 1620, 1560, 7020, 660, 3840, 840, 780, 720, 900, 420, 1320, 660, 480, 840, 1320, 780, 960, 300, 20160, 1620, 600, 600, 2400, 660, 2220, 2220, 2160, 2100, 780, 2100, 480, 1560, 1440, 300, 600, 300, 540, 1620, 900, 1560, 900, 1680, 1620, 1560, 840, 420, 1320, 360, 540, 900, 1740, 1620, 720, 600, 660, 2520, 2460, 900, 900, 28080, 3300, 4320, 3540, 1500, 540, 720, 360, 360, 900, 1260, 660, 300, 420, 420, 720, 300, 3120, 3060, 3900, 3840, 720, 300, 1800, 1560, 240, 360, 1920, 1920, 1920, 1560, 1380, 600, 600, 480, 900, 720, 840, 780, 300, 540, 780, 780, 360, 600, 600, 300, 480, 660, 420, 1200, 240, 1140, 1980, 1980, 840, 480, 840, 1560, 360, 360, 300, 1500, 720, 360, 240, 240, 240, 240, 240, 1200, 1140, 1080, 1020, 1020, 480, 1800, 2220, 2160, 2100, 2100, 480, 600, 480, 780, 1140, 1020, 4620, 4560, 780, 780, 480, 1080, 360, 1440, 540, 1200, 840, 300, 360, 1980, 660, 4680, 4560, 4620, 3480, 240, 3360, 10920, 1080, 540, 300, 180, 960, 1140, 900, 900, 840, 660, 720, 1320, 840, 840, 180, 420, 360, 540, 480, 900, 63240, 180, 600, 360, 480, 1020, 1080, 660, 300, 240, 780, 720, 240, 300, 480, 780, 240, 600, 600, 840, 780, 600, 600, 180, 960, 1680, 1500, 1500, 1380, 1320, 1140, 360, 600, 660, 480, 720, 53100, 300, 540, 1140, 600, 1380, 1680, 1560, 50160, 1020, 3480, 5160, 5160, 1860, 3420, 360, 3180, 4740, 480, 420, 360, 1740, 1680, 1680, 780, 780, 4140, 4080, 3540, 3600, 3480, 660, 480, 600, 540, 480, 480, 300, 480, 3900, 3840, 3720, 36480, 960, 780, 1980, 1860, 31560, 31500, 26280, 360, 1140, 1020, 300, 960, 660, 600, 900, 55080, 420, 420, 960, 780, 180, 1020, 960, 60, 1560, 1440, 1140, 840, 1320, 1140, 1200, 180, 2160, 2100, 240, 1680, 1620, 60, 960, 1440, 61500, 540, 3540, 540, 1140, 240, 27540, 420, 1980, 1200, 180, 1140, 300, 180, 480, 360, 1260, 1320, 300, 300, 360, 8640, 2940, 420, 1440, 240, 480, 960, 240, 300, 840, 840, 540, 720, 1200, 7380, 7320, 7260, 600, 1500, 14700, 1740, 86400, 1320, 1260, 1200, 480, 420, 360, 300, 2220, 900, 3240, 3060, 540, 660, 600, 840, 840, 360, 360, 300, 1920, 1740, 1680, 1560, 6180, 660, 600, 540, 480, 240, 240, 1440, 1440, 1200, 1200, 2040, 480, 3240, 540, 720, 1140, 1080, 1500, 1380, 300, 360, 55500, 180, 660, 2040, 300, 300, 480, 780, 1620, 2580, 2580, 1560, 2460, 180, 1260, 1200, 2220, 1020, 480, 2160, 960, 900, 840, 360, 540, 2040, 1800, 1080, 660, 1680, 780, 2580, 2220, 2520, 1260, 2100, 1260, 3540, 1800, 3480, 180, 420, 5400, 5340, 540, 1620, 1620, 240, 1140, 600, 1080, 960, 2820, 2700, 63180, 420, 720, 780, 1800, 1740, 1680, 1440, 5880, 1380, 5820, 1140, 240, 180, 5700, 360, 5640, 600, 960, 420, 240, 240, 480, 480, 780, 360, 600, 180, 300, 3300, 3240, 660, 480, 1380, 780, 1680, 1620, 3120, 3060, 3060, 3000, 720, 600, 480, 76620, 1140, 300, 1200, 480, 180, 360, 360, 540, 540, 480, 360, 420, 360, 540, 360, 2040, 2760, 1020, 420, 360, 420, 1020, 420, 1320, 1080, 300, 720, 420, 720, 660, 420, 2400, 420, 1200, 1140, 360, 1320, 420, 360, 1620, 1560, 1020, 960, 240, 3360, 3300, 2940, 2700, 600, 420, 120, 360, 480, 840, 480, 300, 120, 300, 600, 240, 60, 60, 60, 10860, 60, 60, 360, 1380, 900, 420, 300, 180, 1020, 360, 780, 480, 660, 600, 780, 16260, 3120, 480, 240, 1140, 900, 8520, 420, 960, 1800, 1740, 13860, 2340, 720, 23700, 480, 1980, 60, 28320, 600, 480, 480, 720, 660, 86400, 240, 420, 660, 420, 240, 600, 660, 900, 840, 4680, 240, 4560, 960, 60, 600, 540, 2400, 2340, 780, 360, 600, 540, 420, 660, 1800, 1680, 960, 7140, 600, 480, 360, 7080, 6840, 6780, 1980, 1740, 240, 240, 480, 660, 360, 960, 180, 540, 660, 720, 120, 360, 1440, 180, 360, 1200, 1380, 1140, 1860, 1080, 1800, 1860, 1740, 720, 600, 1560, 360, 1620, 360, 3540, 3300, 360, 3120, 240, 540, 4020, 960, 86400, 900, 1680, 900, 1320, 540, 2100, 1980, 420, 240, 2100, 60, 840, 480, 240, 1320, 1260, 420, 900, 86400, 1140, 2040, 1080, 1320, 180, 600, 480, 2040, 1980, 780, 1140, 1020, 240, 900, 780, 180, 1020, 360, 540, 480, 1740, 30780, 600, 4860, 4800, 2460, 2520, 600, 2820, 420, 840, 1800, 600, 1080, 1740, 960, 540, 780, 600, 60, 360, 240, 540, 840, 1680, 1680, 300, 360, 900, 180, 420, 1860, 300, 960, 420, 600, 840, 540, 960, 780, 600, 840, 240, 180, 720, 240, 1020, 780, 600, 420, 180, 300, 240, 2280, 1020, 420, 420, 960, 900, 660, 2280, 2220, 1080, 420, 120, 660, 2520, 180, 180, 480, 6780, 360, 360, 660, 3420, 3480, 480, 540, 1320, 180, 420, 120, 420, 60, 60, 44100, 480, 960, 600, 1440, 1440, 360, 540, 420, 600, 24000, 26880, 600, 420, 180, 300, 900, 480, 360, 360, 420, 480, 720, 600, 420, 480, 34440, 1380, 360, 360, 780, 540, 10920, 300, 240, 240, 480, 420, 360, 960, 960, 360, 540, 480, 420, 2400, 420, 8700, 2280, 780, 120, 1440, 480, 300, 300, 540, 420, 1200, 420, 1080, 420, 540, 720, 540, 240, 420, 720, 600, 540, 660, 2520, 3660, 360, 420, 900, 960, 540, 660, 720, 540, 60, 960, 38880, 1620, 1440, 660, 180, 540, 12360, 780, 3720, 3660, 360, 660, 480, 180, 480, 240, 3180, 420, 660, 780, 300, 240, 540, 360, 1020, 660, 960, 720, 6060, 420, 900, 6000, 5880, 240, 540, 540, 600, 180, 840, 480, 660, 600, 180, 420, 4800, 4740, 8520, 8400, 8640, 3840, 360, 3780, 300, 840, 120, 1200, 1140, 360, 480, 900, 240, 360, 120, 540, 540, 420, 360, 540, 420, 540, 660, 900, 540, 660, 240, 480, 900, 1020, 540, 600, 660, 480, 180, 840, 480, 4200, 3240, 300, 240, 1800, 240, 900, 1260, 300, 420, 660, 420, 1020, 840, 240, 720, 660, 420, 360, 600, 420, 420, 360, 180, 480, 480, 480, 720, 120, 840, 300, 180, 540, 780, 660, 480, 780, 840, 360, 300, 1500, 360, 420, 600, 540, 540, 360, 1260, 480, 240, 1020, 1020, 660, 240, 420, 300, 1200, 1140, 720, 480, 1560, 180, 840, 780, 660, 900, 660, 540, 12720, 540, 600, 240, 960, 600, 300, 360, 1620, 480, 86400, 660, 540, 480, 180, 1140, 600, 960, 900, 180, 420, 540, 300, 300, 60, 780, 780, 960, 600, 420, 600, 900, 480, 480, 240, 720, 720, 420, 480, 120, 540, 1140, 420, 600, 720, 420, 540, 300, 180, 300, 540, 480, 480, 300, 660, 480, 360, 180, 46080, 1200, 360, 780, 360, 240, 420, 300, 240, 840, 360, 600, 600, 720, 360, 660, 1260, 960, 420, 780, 900, 300, 480, 300, 180, 180, 240, 3780, 420, 420, 360, 600, 300, 300, 780, 1260, 300, 38160, 420, 720, 720, 360, 360, 3720, 2160, 1320, 2100, 1260, 300, 600, 5340, 300, 180, 960, 960, 60, 480, 360, 2160, 900, 720, 480, 1560, 840, 420, 1320, 240, 360, 600, 480, 4680, 360, 4620, 840, 300, 360, 300, 420, 540, 960, 1860, 300, 900, 480, 420, 1320, 660, 3780, 720, 300, 960, 900, 240, 360, 300, 780, 360, 540, 660, 840, 420, 300, 180, 840, 1020, 180, 420, 240, 360, 240, 900, 300, 600, 120, 180, 780, 420, 300, 540, 1080, 480, 840, 1560, 420, 720, 720, 420, 420, 480, 420, 1080, 300, 960, 360, 180, 27420, 720, 660, 960, 1020, 60, 240, 480, 240, 360, 1500, 300, 660, 240, 1020, 2100, 240, 540, 300, 540, 1560, 360, 420, 420, 180, 660, 180, 1380, 300, 1800, 1680, 360, 660, 2280, 180, 2220, 2160, 2160, 420, 480, 780, 1320, 780, 840, 480, 5820, 360, 840, 300, 480, 360, 240, 540, 300, 480, 3660, 420, 420, 600, 240, 420, 480, 660, 660, 480, 240, 180, 2700, 420, 480, 420, 60, 3060, 3060, 1380, 480, 840, 360, 360, 120, 240, 840, 900, 600, 780, 1980, 720, 360, 900, 1260, 1200, 600, 360, 360, 240, 3540, 3600, 1200, 780, 420, 360, 300, 300, 960, 420, 600, 480, 480, 420, 2940, 2880, 480, 960, 1260, 420, 10980, 600, 86400, 900, 300, 120, 2700, 420, 240, 960, 960, 420, 540, 4320, 840, 4320, 1560, 180, 12300, 1320, 840, 1860, 420, 780, 420, 300, 35220, 660, 540, 660, 1620, 240, 240, 300, 780, 420, 900, 1020, 960, 300, 240, 480, 300, 360, 360, 300, 600, 180, 4680, 1020, 720, 900, 480, 240, 480, 420, 660, 840, 360, 600, 480, 360, 840, 1500, 180, 420, 120, 3000, 720, 300, 180, 2940, 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In [70]:
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trendsD=[];
for i in range(len(df)):
    if tripRouteCategories[i]!='Round Trip' and math.isnan(startingLatitudes[i])==False and math.isnan(startingLongitudes[i])==False and math.isnan(endingLatitudes[i])==False and math.isnan(endingLongitudes[i])==False and startingLatitudes[i]!=0.0 and startingLongitudes[i]!=0.0 and endingLatitudes[i]!=0.0 and endingLongitudes[i]!=0.0:
        trendsduration.append(durations[i])
        firstPointCoords=(startingLatitudes[i], startingLongitudes[i])
        secondPointCoords=(endingLatitudes[i], endingLongitudes[i])
        distance=geopy.distance.vincenty(firstPointCoords, secondPointCoords).miles
        trendsD.append(distance)
print trendsduration, trendsD
    
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600, 120, 180, 180, 240, 300, 540, 180, 120, 600, 900, 360, 2040, 1080, 240, 420, 360, 180, 960, 180, 420, 360, 360, 720, 1500, 1380, 300, 480, 720, 1920, 1920, 780, 720, 660, 2100, 2400, 1260, 420, 1620, 1620, 420, 1020, 720, 960, 300, 240, 240, 240, 960, 1200, 1200, 420, 360, 1440, 180, 180, 180, 900, 300, 180, 1140, 1620, 1620, 780, 780, 300, 660, 600, 1500, 1260, 1380, 1380, 900, 1020, 1020, 240, 1860, 600, 1440, 1380, 1320, 300, 540, 480, 1380, 1140, 120, 900, 480, 600, 1380, 360, 780, 1020, 1020, 1020, 420, 360, 180, 720, 1140, 240, 1020, 180, 900, 600, 840, 900, 1080, 720, 780, 180, 420, 1140, 1080, 1860, 960, 1260, 900, 420, 900, 660, 660, 600, 900, 720, 300, 420, 360, 120, 3900, 480, 600, 780, 480, 420, 300, 420, 720, 480, 900, 480, 660, 1800, 360, 600, 840, 720, 840, 720, 840, 480, 1380, 180, 900, 1260, 240, 1560, 300, 480, 720, 300, 1560, 120, 1500, 1320, 360, 1320, 720, 840, 480, 540, 720, 660, 660, 240, 1020, 960, 660, 600, 600, 480, 720, 720, 300, 480, 240, 1560, 1080, 1020, 1740, 480, 240, 240, 660, 840, 780, 420, 420, 900, 900, 180, 900, 600, 540, 720, 780, 540, 1080, 660, 240, 720, 720, 180, 960, 600, 600, 540, 600, 1200, 1140, 600, 600, 360, 540, 300, 660, 540, 7080, 480, 300, 480, 720, 1020, 960, 36060, 600, 480, 660, 900, 360, 540, 1140, 1140, 600, 240, 300, 600, 2100, 2160, 1740, 1080, 840, 1080, 780, 960, 900, 480, 540, 240, 420, 480, 900, 1800, 420, 660, 780, 540, 5280, 360, 180, 5760, 240, 840, 240, 540, 7260, 480, 420, 780, 120, 360, 420, 660, 300, 720, 900, 900, 840, 600, 180, 2100, 480, 840, 540, 900, 1500, 420, 1440, 540, 540, 1080, 300, 780, 360, 840, 720, 360, 660, 780, 480, 660, 600, 780, 480, 660, 300, 360, 540, 240, 240, 240, 420, 540, 600, 480, 420, 480, 480, 480, 300, 360, 720, 180, 180, 180, 120, 600, 720, 480, 420, 240, 600, 360, 480, 480, 480, 300, 480, 1080, 360, 720, 180, 180, 240, 180, 180, 120, 600, 540, 1740, 240, 240, 180, 180, 120, 120, 420, 180, 900, 480, 480, 240, 240, 240, 780, 780, 660, 240, 1020, 180, 180, 180, 180, 420, 300, 120, 120, 180, 120, 420, 360, 600, 720, 300, 960, 1020, 480, 540, 600, 540, 960, 900, 720, 1020, 660, 540, 1260, 1260, 3900, 1200, 360, 900, 300, 360, 300, 3840, 540, 720, 780, 3060, 540, 1980, 1980, 180, 240, 600, 300, 540, 420, 1620, 720, 1440, 540, 420, 1140, 120, 780, 360, 1140, 540, 540, 480, 300, 300, 300, 300, 300, 480, 660, 240, 600, 480, 180, 360, 300, 1800, 480, 1080, 540, 600, 420, 240, 240, 480, 420, 180, 1800, 240, 240, 240, 240, 420, 180, 840, 1080, 360, 660, 660, 660, 660, 300, 540, 960, 3780, 1140, 540, 840, 840, 1920, 300, 300, 240, 180, 180, 180, 180, 1560, 780, 660, 540, 420, 240, 240, 240, 240, 420, 420, 660, 180, 180, 180, 180, 840, 360, 360, 360, 480, 240, 600, 1320, 960, 1620, 840, 300, 300, 300, 720, 720, 540, 780, 960, 480, 540, 5160, 900, 360, 780, 780, 480, 1500, 2760, 660, 240, 960, 960, 5700, 420, 1140, 480, 1260, 1200, 300, 1080, 1080, 480, 480, 420, 1260, 720, 300, 120, 1020, 660, 1980, 840, 660, 780, 1740, 720, 360, 720, 780, 1200, 480, 1080, 540, 960, 180, 600, 420, 480, 420, 420, 360, 360, 360, 960, 480, 480, 720, 1020, 360, 840, 240, 660, 300, 1440, 720, 540, 1260, 300, 900, 540, 840, 660, 2460, 840, 240, 720, 720, 240, 840, 1200, 1020, 360, 180, 480, 480, 660, 300, 1560, 720, 1200, 540, 840, 240, 360, 1140, 900, 840, 1080, 1080, 360, 480, 480, 360, 660, 1020, 360, 960, 900, 1080, 540, 480, 960, 420, 660, 660, 540, 1140, 180, 660, 3600, 360, 1020, 960, 660, 720, 480, 1500, 1320, 1140, 540, 360, 240, 360, 240, 300, 1980, 1020, 420, 540, 540, 480, 240, 780, 1740, 1320, 1200, 960, 840, 480, 600, 540, 420, 480, 180, 240, 1080, 600, 1080, 1080, 720, 720, 360, 600, 780, 240, 360, 300, 660, 600, 480, 1680, 1260, 360, 780, 780, 1080, 780, 720, 240, 1320, 420, 420, 120, 480, 120, 540, 120, 1320, 420, 1260, 120, 960, 480, 360, 480, 480, 240, 240, 240, 120, 300, 420, 300, 420, 120, 180, 780, 720, 420, 1080, 420, 780, 1620, 720, 480, 780, 660, 660, 1020, 240, 840, 420, 300, 180, 960, 120, 540, 420, 660, 480, 240, 840, 960, 240, 360, 420, 960, 600, 480, 720, 360, 900, 720, 1200, 600, 840, 420, 660, 780, 720, 300, 420, 540, 240, 660, 240, 1020, 600, 540, 540, 1440, 1020, 720, 2160, 780, 660, 660, 300, 2160, 900, 540, 480, 240, 360, 480, 300, 720, 300, 300, 240, 540, 540, 480, 360, 540, 180, 720, 120, 120, 120, 120, 1380, 1260, 1200, 1200, 1200, 540, 360, 780, 420, 1560, 360, 660, 360, 660, 480, 480, 420, 360, 240, 2460, 3000, 1800, 2220, 2220, 2220, 660, 600, 46260, 420, 660, 900, 180, 420, 720, 4020, 720, 780, 840, 720, 360, 1080, 1320, 1020, 960, 660, 540, 120, 540, 420, 720, 240, 480, 720, 300, 480, 180, 840, 780, 2760, 780, 480, 360, 1080, 540, 540, 2100, 240, 960, 1680, 540, 480, 1140, 240, 1260, 660, 660, 900, 600, 600, 840, 720, 780, 840, 660, 660, 660, 360, 720, 720, 240, 300, 540, 540, 480, 480, 780, 540, 540, 240, 660, 660, 360, 420, 960, 1740, 660, 480, 300, 240, 300, 300, 240, 240, 660, 540, 1020, 1020, 360, 720, 540, 300, 600, 780, 240, 2520, 540, 1080, 360, 900, 840, 480, 300, 180, 360, 360, 420, 1260, 540, 480, 540, 900, 180, 720, 780, 540, 240, 1200, 420, 480, 840, 660, 660, 300, 480, 180, 1140, 900, 960, 2280, 1680, 1680, 1020, 2820, 1020, 960, 480, 780, 420, 420, 1080, 960, 600, 1080, 720, 1140, 660, 240, 780, 720, 300, 840, 25740, 900, 780, 960, 840, 1200, 540, 720, 11700, 720, 360, 900, 600, 300, 420, 360, 180, 360, 660, 720, 420, 1200, 1200, 360, 780, 300, 1020, 960, 540, 660, 360, 5760, 660, 420, 420, 4380, 1560, 600, 960, 540, 300, 840, 1020, 1200, 960, 960, 600, 900, 600, 180, 300, 480, 540, 240, 360, 1020, 420, 420, 300, 780, 300, 2040, 1440, 540, 420, 1020, 480, 420, 180, 420, 420, 540, 840, 600, 300, 360, 1380, 420, 360, 960, 720, 1380, 420, 240, 180, 840, 660, 660, 660, 660, 360, 540, 840, 2820, 960, 8460, 300, 1080, 1080, 360, 300, 480, 1860, 660, 540, 960, 420, 480, 1500, 120, 900, 1020, 1320, 960, 300, 300, 840, 1080, 420, 900, 420, 480, 240, 360, 540, 960, 1200, 2040, 840, 540, 660, 1500, 540, 960, 960, 180, 780, 660, 180, 1020, 1620, 240, 480, 480, 300, 960, 960, 420, 1680, 780, 660, 900, 1080, 1020, 1260, 180, 1080, 300, 300, 300, 540, 360, 360, 480, 600, 8640, 780, 780, 780, 780, 780, 720, 720, 540, 1140, 1140, 2340, 420, 420, 540, 540, 1260, 1080, 360, 1200, 540, 240, 180, 300, 300, 300, 540, 1020, 600, 600, 780, 1380, 1380, 480, 120, 600, 360, 600, 1620, 780, 2640, 360, 21780, 20820, 1620, 600, 480, 480, 420, 360, 840, 180, 840, 1140, 360, 240, 180, 240, 600, 600, 960, 300, 840, 300, 120, 540, 420, 900, 540, 5940, 360, 360, 540, 420, 240, 240, 1020, 180, 240, 1020, 480, 780, 900, 840, 1200, 900, 300, 780, 300, 840, 960, 1080, 720, 720, 300, 600, 480, 780, 660, 600, 2700, 660, 360, 300, 840, 240, 780, 660, 480, 480, 1140, 1740, 420, 600, 1320, 1140, 1140, 360, 720, 720, 480, 660, 540, 2040, 1020, 3300, 900, 240, 13440, 13440, 1740, 240, 480, 1020, 240, 300, 120, 480, 360, 240, 480, 660, 360, 660, 240, 240, 480, 240, 300, 360, 720, 720, 360, 600, 660, 540, 840, 960, 900, 660, 660, 180, 240, 420, 1500, 1440, 1080, 1380, 1380, 1320, 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0.47325339184928455, 0.4165436815334033, 0.2982949243000364, 0.6592867621683023, 0.1824235952270147, 0.19300857679210306, 0.664707991510587, 0.664707991510587, 0.48465798506587815, 0.48465798506587815, 0.3266854778036171, 0.18345239245423678, 1.0338132452030833, 1.0338132452030833, 1.496205714899629, 0.8290135817687184, 1.0325172214367648, 0.8290135817687184, 1.471157087375703, 1.0325172214367648, 0.8735106145757333, 0.6241833906247439, 1.0379747838822106, 0.6241833906247439, 1.474547145212976, 0.4479667073131044, 0.9288512664480724, 0.7468498295428461, 0.5108019649979113, 0.5246242876958841, 0.8225527176609492, 0.3836432021632936, 1.1069189657206095, 0.6358462235944394, 0.32634360916357863, 0.43793172906703265, 0.3649907738251005, 0.46873492194348837, 1.299237200560644, 0.5108019649979596, 0.573606110136746, 1.4777722756928564, 0.7167459529471086, 0.9271642876918774, 1.3466179451601668, 0.8233179334435177, 1.2122561332011397, 0.6787863276919422, 0.4474344618998073, 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In [71]:
plt.plot(trendsduration, trendsD, 'o')
plt.title("Time vs. Distance Covered per Ride (Speed)")
plt.xlabel("Duration (Seconds)")
plt.ylabel("Distance Covered (miles)")
plt.show()

The graph above tells us the speed of each ride. According to the data, the speeds vary greatly, even when riders travel the same distance. However, most of the data points do seem to be bunched up near the bottom left corner, indicating maybe around less than 0-3 miles is the most common distance covered and that around 0-2000 seconds is the most common duration per ride. The axis intervals can be manipulated in order to more clearly see trends in the data (this is a common theme for most of my graphs).

In [226]:
starting_station_ids=[]
for row in df["Starting Station ID"]:
    starting_station_ids.append(row)
print starting_station_ids
[3014.0, 3014.0, 3016.0, 3016.0, 3032.0, 3021.0, 3022.0, 3076.0, 3031.0, 3031.0, 3031.0, 3063.0, 3042.0, 3018.0, 3054.0, 3031.0, 3006.0, 3018.0, 3014.0, 3037.0, 3018.0, 3063.0, 3034.0, 3063.0, 3016.0, 3005.0, 3005.0, 3018.0, 3047.0, 3037.0, 3040.0, 3040.0, 3014.0, 3066.0, 3037.0, 3016.0, 3014.0, 3033.0, 3030.0, 3033.0, 3034.0, 3031.0, 3022.0, 3030.0, 3030.0, 3022.0, 3030.0, 3037.0, 3030.0, 3006.0, 3063.0, 3066.0, 3066.0, 3063.0, 3051.0, 3030.0, 3019.0, 3030.0, 3030.0, 3006.0, 3006.0, 3033.0, 3054.0, 3014.0, 3030.0, 3055.0, 3018.0, 3006.0, 3065.0, 3068.0, 3014.0, 3018.0, 3018.0, 3047.0, 3076.0, 3007.0, 3030.0, 3006.0, 3047.0, 3018.0, 3031.0, 3052.0, 3019.0, 3065.0, 3016.0, 3076.0, 3019.0, 3065.0, 3030.0, 3014.0, 3047.0, 3049.0, 3030.0, 3014.0, 3063.0, 3005.0, 3075.0, 3068.0, 3030.0, 3005.0, 3052.0, 3034.0, 3040.0, 3040.0, 3016.0, 3032.0, 3040.0, 3016.0, 3067.0, 3066.0, 3034.0, 3066.0, 3005.0, 3014.0, 3005.0, 3020.0, 3019.0, 3014.0, 3021.0, 3063.0, 3034.0, 3042.0, 3005.0, 3042.0, 3042.0, 3066.0, 3020.0, 3016.0, 3067.0, 3030.0, 3049.0, 3021.0, 3021.0, 3016.0, 3014.0, 3032.0, 3055.0, 3049.0, 3035.0, 3042.0, 3005.0, 3067.0, 3006.0, 3067.0, 3052.0, 3052.0, 3022.0, 3052.0, 3063.0, 3051.0, 3031.0, 3018.0, 3018.0, 3030.0, 3030.0, 3021.0, 3022.0, 3062.0, 3062.0, 3035.0, 3034.0, 3049.0, 3021.0, 3014.0, 3006.0, 3035.0, 3034.0, 3034.0, 3042.0, 3030.0, 3014.0, 3055.0, 3042.0, 3066.0, 3042.0, 3058.0, 3045.0, 3051.0, 3005.0, 3021.0, 3021.0, 3032.0, 3080.0, 3021.0, 3021.0, 3021.0, 3021.0, 3037.0, 3037.0, 3033.0, 3014.0, 3038.0, 3035.0, 3067.0, 3067.0, 3005.0, 3075.0, 3075.0, 3038.0, 3049.0, 3021.0, 3022.0, 3034.0, 3049.0, 3018.0, 3075.0, 3005.0, 3063.0, 3042.0, 3014.0, 3062.0, 3053.0, 3031.0, 3055.0, 3031.0, 3066.0, 3014.0, 3038.0, 3014.0, 3030.0, 3069.0, 3034.0, 3036.0, 3045.0, 3055.0, 3042.0, 3037.0, 3058.0, 3079.0, 3045.0, 3047.0, 3045.0, 3005.0, 3030.0, 3038.0, 4108.0, 3080.0, 3036.0, 3036.0, 3052.0, 3060.0, 3042.0, 3014.0, 3008.0, 3019.0, 3038.0, 3035.0, 3058.0, 3066.0, 3018.0, 3056.0, 3016.0, 3030.0, 3030.0, 3030.0, 3030.0, 3069.0, 3032.0, 3014.0, 3006.0, 3014.0, 3016.0, 3030.0, 3030.0, 3068.0, 3007.0, 3014.0, 3014.0, 3019.0, 3076.0, 3065.0, 3065.0, 3042.0, 3030.0, 3006.0, 3006.0, 3022.0, 3016.0, 3069.0, 3006.0, 3030.0, 3062.0, 3029.0, 3055.0, 3021.0, 3021.0, 3016.0, 3065.0, 3051.0, 3016.0, 3030.0, 3006.0, 3006.0, 3022.0, 3036.0, 3022.0, 3005.0, 3005.0, 3008.0, 3042.0, 3063.0, 3035.0, 3049.0, 3028.0, 3028.0, 3042.0, 3021.0, 3051.0, 3076.0, 3036.0, 3075.0, 3075.0, 3042.0, 3055.0, 3056.0, 3063.0, 3066.0, 3030.0, 3034.0, 3040.0, 3065.0, 3036.0, 3065.0, 3022.0, 3005.0, 3020.0, 3068.0, 3030.0, 3062.0, 3019.0, 3038.0, 3067.0, 3014.0, 3014.0, 3069.0, 3034.0, 3035.0, 3042.0, 3014.0, 3062.0, 3014.0, 3023.0, 3028.0, 3028.0, 3034.0, 3007.0, 3007.0, 3063.0, 3062.0, 3069.0, 3052.0, 3028.0, 3069.0, 3068.0, 3014.0, 3035.0, 3006.0, 3060.0, 3055.0, 3055.0, 3028.0, 3019.0, 3075.0, 3020.0, 3035.0, 3058.0, 3006.0, 3032.0, 3035.0, 3035.0, 3032.0, 3036.0, 3052.0, 3076.0, 3035.0, 3076.0, 3035.0, 3040.0, 3038.0, 3035.0, 3035.0, 3030.0, 3079.0, 3065.0, 3063.0, 3069.0, 3032.0, 3049.0, 3030.0, 3005.0, 3036.0, 3005.0, 3005.0, 3075.0, 3053.0, 3006.0, 3052.0, 3054.0, 3034.0, 3022.0, 3038.0, 3035.0, 3028.0, 3063.0, 3025.0, 3016.0, 3022.0, 3074.0, 3053.0, 3007.0, 3057.0, 3038.0, 3005.0, 3006.0, 3006.0, 3021.0, 3067.0, 3036.0, 3042.0, 3042.0, 3031.0, 3030.0, 3034.0, 3040.0, 3040.0, 3034.0, 3049.0, 3005.0, 3075.0, 3068.0, 3075.0, 3007.0, 3014.0, 3022.0, 3014.0, 3055.0, 3036.0, 3051.0, 3006.0, 3014.0, 3014.0, 3016.0, 3006.0, 3014.0, 3016.0, 3005.0, 3066.0, 3032.0, 3065.0, 3030.0, 3027.0, 3027.0, 3005.0, 3054.0, 3005.0, 3005.0, 3069.0, 3037.0, 3028.0, 3006.0, 3074.0, 3031.0, 3031.0, 3075.0, 3075.0, 3067.0, 3022.0, 3022.0, 3014.0, 3005.0, 3052.0, 3042.0, 3052.0, 3052.0, 3028.0, 3006.0, 3021.0, 3018.0, 3058.0, 3058.0, 3030.0, 3030.0, 3036.0, 3031.0, 3065.0, 3065.0, 3062.0, 3058.0, 3058.0, 3026.0, 3005.0, 3031.0, 3031.0, 3038.0, 3047.0, 3035.0, 3052.0, 3067.0, 3067.0, 3005.0, 3035.0, 3075.0, 3065.0, 3065.0, 3035.0, 3038.0, 3035.0, 3069.0, 3038.0, 3047.0, 3047.0, 3016.0, 3016.0, 3006.0, 3068.0, 3062.0, 3062.0, 3067.0, 3005.0, 3005.0, 3062.0, 3062.0, 3058.0, 3058.0, 3014.0, 3014.0, 3023.0, 3023.0, 3074.0, 3006.0, 3047.0, 3063.0, 3063.0, 3006.0, 3006.0, 3075.0, 3016.0, 3056.0, 3056.0, 3021.0, 3038.0, 3038.0, 3018.0, 3018.0, 3037.0, 3063.0, 3063.0, 3026.0, 3067.0, 3055.0, 3056.0, 3057.0, 3006.0, 3038.0, 3021.0, 3058.0, 3062.0, 3053.0, 3023.0, 3057.0, 3006.0, 3075.0, 3075.0, 3049.0, 3049.0, 3021.0, 3032.0, 3037.0, 3037.0, 3037.0, 3022.0, 3034.0, 3034.0, 3074.0, 3005.0, 3078.0, 3034.0, 3021.0, 3021.0, 3067.0, 3068.0, 3031.0, 3031.0, 3047.0, 3055.0, 3057.0, 3031.0, 3038.0, 3069.0, 3031.0, 3075.0, 3075.0, 3006.0, 3049.0, 3069.0, 3074.0, 3031.0, 3031.0, 3074.0, 3057.0, 3038.0, 3029.0, 3022.0, 3067.0, 3023.0, 3075.0, 3075.0, 3042.0, 3030.0, 3035.0, 3035.0, 3030.0, 3067.0, 3032.0, 3030.0, 3021.0, 3078.0, 3055.0, 3049.0, 3033.0, 3022.0, 3037.0, 3031.0, 3008.0, 3066.0, 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3046.0, 3034.0, 3048.0, 3047.0, 3018.0, 3048.0, 3052.0, 3014.0, 3024.0, 3030.0, 3038.0, 3005.0, 3078.0, 3082.0, 3047.0, 3052.0, 3069.0, 3046.0, 3069.0, 3018.0, 3042.0, 3075.0, 3022.0, 3048.0, 3027.0, 3029.0, 3036.0, 3032.0, 3042.0, 3076.0, 3076.0, 3030.0, 3075.0, 3014.0, 3067.0, 3067.0, 3014.0, 3019.0, 3016.0, 3026.0, 3030.0, 3019.0, 3046.0, 3046.0, 3046.0, 3031.0, 3069.0, 3068.0, 3066.0, 3019.0, 3064.0, 3067.0, 3067.0, 3057.0, 3057.0, 3052.0, 3066.0, 3020.0, 3020.0, 3020.0, 3029.0, 3030.0, 3019.0, 3064.0, 3047.0, 3069.0, 3051.0, 3056.0, 3056.0, 3014.0, 3008.0, 3008.0, 3037.0, 3022.0, 3051.0, 3032.0, 3075.0, 3056.0, 3065.0, 3082.0, 3067.0, 3051.0, 3051.0, 3031.0, 3034.0, 3051.0, 3007.0, 3019.0, 3047.0, 3007.0, 3019.0, 3062.0, 3007.0, 3007.0, 3019.0, 3028.0, 3054.0, 3022.0, 3064.0, 3020.0, 3020.0, 3020.0, 3074.0, 3068.0, 3052.0, 3052.0, 3006.0, 3064.0, 3030.0, 3035.0, 3035.0, 3035.0, 3033.0, 3006.0, 3054.0, 3030.0, 3006.0, 3075.0, 3042.0, 3030.0, 3075.0, 3030.0, 3022.0, 3081.0, 3016.0, 3048.0, 3048.0, 3069.0, 3052.0, 3078.0, 3028.0, 3028.0, 3069.0, 3007.0, 3049.0, 3031.0, 3016.0, 3031.0, 3057.0, 3077.0, 3029.0, 3074.0, 3082.0, 3064.0, 3063.0, 3074.0, 3067.0, 3022.0, 3038.0, 3018.0, 3047.0, 3037.0, 3031.0, 3056.0, 3030.0, 3030.0, 3025.0, 3062.0, 3074.0, 3007.0, 3048.0, 3060.0, 3060.0, 3060.0, 3030.0, 3022.0, 3062.0, 3031.0, 3062.0, 3048.0, 3068.0, 3081.0, 3031.0, 3069.0, 3052.0, 3027.0, 3067.0, 3069.0, 3069.0, 3069.0, 3056.0, 3011.0, 3048.0, 3005.0, 3052.0, 3005.0, 3052.0, 3052.0, 3022.0, 3063.0, 3031.0, 3018.0, 3018.0, 3032.0, 3074.0, 3068.0, 3019.0, 3030.0, 3031.0, 3030.0, 3016.0, 3068.0, 3030.0, 3027.0, 3054.0, 3056.0, 3054.0, 3066.0, 3018.0, 3064.0, 3055.0, 3052.0, 3028.0, 3027.0, 3064.0, 3030.0, 3030.0, 3027.0, 3020.0, 3014.0, 3075.0, 3075.0, 3064.0, 3007.0, 3024.0, 3062.0, 3067.0, 3032.0, 3019.0, 3076.0, 3029.0, 3027.0, 3082.0, 3048.0, 3014.0, 3014.0, 3014.0, 3076.0, 3014.0, 3032.0, 3049.0, 3031.0, 3007.0, 3023.0, 3007.0, 3038.0, 3007.0, 3064.0, 3068.0, 3049.0, 3063.0, 3037.0, 3069.0, 3019.0, 3030.0, 3056.0, 3068.0, 3049.0, 3019.0, 3035.0, 3068.0, 3035.0, 3055.0, 3055.0, 3005.0, 3030.0, 3055.0, 3031.0, 3060.0, 3069.0, 3081.0, 3081.0, 3042.0, 3033.0, 3068.0, 3042.0, 3028.0, 3022.0, 3028.0, 3034.0, 3007.0, 3078.0, 3054.0, 3006.0, 3006.0, 3075.0, 3069.0, 3066.0, 3066.0, 3048.0, 3034.0, 3075.0, 3075.0, 3029.0, 3030.0, 3030.0, 3046.0, 3055.0, 3078.0, 3007.0, 3007.0, 3007.0, 3023.0, 3023.0, 3078.0, 3082.0, 3028.0, 3077.0, 3035.0, 3055.0, 3077.0, 3030.0, 3069.0, 3022.0, 3047.0, 3005.0, 3047.0, 3005.0, 3038.0, 3042.0, 3051.0, 3047.0, 3035.0, 3064.0, 3079.0, 3048.0, 3063.0, 3078.0, 3038.0, 3082.0, 3022.0, 3006.0, 3045.0, 3022.0, 3064.0, 3005.0, 3075.0, 3068.0, 3052.0, 3023.0, 3062.0, 3030.0, 3046.0, 3026.0, 3028.0, 3038.0, 3005.0, 3005.0, 3081.0, 3081.0, 3064.0, 3006.0, 3074.0, 3008.0, 3014.0, 3031.0, 3049.0, 3006.0, 3049.0, 3031.0, 3031.0, 3031.0, 3047.0, 3067.0, 3054.0, 3054.0, 3036.0, 3005.0, 3031.0, 3029.0, 3006.0, 3006.0, 3068.0, 3037.0, 3037.0, 3031.0, 3030.0, 3022.0, 3055.0, 3082.0, 3082.0, 3007.0, 3067.0, 3051.0, 3035.0, 3028.0, 3007.0, 3028.0, 3022.0, 3022.0, 3052.0, 3052.0, 3052.0, 3069.0, 3030.0, 3051.0, 3082.0, 3082.0, 3062.0, 3064.0, 3005.0, 3016.0, 3038.0, 3030.0, 3063.0, 3014.0, 3049.0, 3031.0, 3078.0, 3064.0, 3042.0, 3014.0, 3049.0, 3082.0, 3047.0, 3049.0, 3027.0, 3066.0, 3023.0, 3023.0, 3023.0, 3067.0, 3074.0, 3055.0, 3082.0, 3023.0, 3067.0, 3049.0, 3018.0, 3014.0, 3052.0, 3014.0, 3014.0, 3075.0, 3033.0, 3038.0, 3029.0, 3029.0, 3025.0, 3034.0, 3058.0, 3000.0, 3000.0, 3000.0, 3030.0, 3026.0, 3076.0, 3076.0, 3069.0, 3055.0, 3038.0, 3006.0, 3014.0, 3042.0, 3027.0, 3040.0, 3062.0, 3014.0, 3042.0, 3067.0, 3032.0, 3042.0, 3055.0, 3025.0, 3062.0, 3047.0, 3040.0, 3034.0, 3069.0, 3062.0, 3069.0, 3069.0, 3067.0, 3031.0, 3082.0, 3022.0, 3032.0, 3042.0, 3025.0, 3042.0, 3042.0, 3049.0, 3040.0, 3042.0, 3066.0, 3081.0, 3076.0, 3062.0, 3082.0, 3055.0, 3005.0, 3081.0, 3068.0, 3006.0, 3038.0, 3067.0, 3035.0, 3060.0, 3060.0, 3068.0, 3064.0, 3014.0, 3047.0, 3027.0, 3038.0, 3060.0, 3049.0, 3049.0, 3008.0, 3038.0, 3023.0, 3052.0, 3035.0, 3055.0, 3038.0, 3011.0, 3011.0, 3027.0, 3005.0, 3054.0, 3082.0, 3034.0, 3016.0, 3016.0, 3019.0, 3014.0, 3019.0, 3019.0, 3052.0, 3019.0, 3019.0, 3019.0, 3019.0, 3049.0, 3022.0, 3063.0, 3046.0, 3074.0, 3007.0, 3067.0, 3023.0, 3035.0, 3005.0, 3052.0, 3067.0, 3069.0, 3023.0, 3069.0, 3022.0, 3069.0, 3008.0, 3008.0, 3008.0, 3008.0, 3008.0, 3022.0, 3019.0, 3008.0, 3047.0, 3018.0, 3052.0, 3063.0, 3063.0, 3056.0, 3056.0, 3074.0, 3068.0, 3075.0, 3067.0, 3027.0, 3062.0, 3082.0, 3006.0, 3042.0, 3040.0, 3067.0, 3068.0, 3008.0, 3068.0, 3075.0, 3075.0, 3075.0, 3019.0, 3023.0, 3019.0, 3008.0, 3027.0, 3063.0, 3007.0, 3058.0, 3005.0, 3006.0, 3030.0, 3069.0, 3054.0, 3026.0, 3030.0, 3007.0, 3069.0, 3030.0, 3064.0, 3026.0, 3056.0, 3069.0, 3067.0, 3031.0, 3064.0, 3064.0, 3028.0, 3038.0, 3076.0, 3068.0, 3027.0, 3026.0, 3027.0, 3011.0, 3022.0, 3022.0, 3047.0, 3055.0, 3047.0, 3014.0, 3074.0, 3011.0, 3011.0, 3011.0, 3011.0, 3011.0, 3011.0, 3011.0, 3064.0, 3068.0, 3063.0, 3038.0, 3064.0, 3038.0, 3011.0, 3005.0, 3031.0, 3032.0, 3038.0, 3030.0, 3007.0, 3056.0, 3076.0, 3076.0, 3030.0, 3011.0, 3011.0, 3069.0, 3069.0, 3076.0, 3014.0, 3031.0, 3022.0, 3037.0, 3022.0, 3014.0, 3022.0, 3067.0, 3055.0, 3005.0, 3069.0, 3040.0, 3048.0, 3069.0, 3074.0, 3058.0, 3058.0, 3047.0, 3048.0, 3058.0, 3027.0, 3054.0, 3035.0, 3064.0, 3040.0, 3040.0, 3014.0, 3014.0, 3048.0, 3066.0, 3051.0, 3016.0, 3056.0, 3032.0, 3035.0, 3005.0, 3047.0, 3031.0, 3049.0, 3027.0, 3048.0, 3074.0, 3030.0, 3030.0, 3030.0, 3030.0, 3008.0, 3056.0, 3048.0, 3048.0, 3026.0, 3055.0, 3042.0, 3055.0, 3051.0, 3042.0, 3042.0, 3074.0, 3042.0, 3076.0, 3080.0, 3042.0, 3076.0, 3023.0, 3035.0, 3014.0, 3078.0, 3068.0, 3054.0, 3055.0, 3024.0, 3051.0, 3082.0, 3076.0, 3030.0, 3029.0, 3023.0, 3007.0, 3079.0, 3022.0, 3038.0, 3075.0, 3047.0, 3051.0, 3011.0, 3052.0, 3014.0, 3024.0, 3051.0, 3010.0, 3048.0, 3030.0, 3049.0, 3049.0, 3048.0, 3011.0, 3074.0, 3055.0, 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In [267]:
speeds=[]
selectStartingStationIDs=[]
for i in range(len(df)):
    if tripRouteCategories[i]!='Round Trip' and math.isnan(startingLatitudes[i])==False and math.isnan(startingLongitudes[i])==False and math.isnan(endingLatitudes[i])==False and math.isnan(endingLongitudes[i])==False and startingLatitudes[i]!=0.0 and startingLongitudes[i]!=0.0 and endingLatitudes[i]!=0.0 and endingLongitudes[i]!=0.0:
        trendsduration.append(durations[i])
        firstPointCoords=(startingLatitudes[i], startingLongitudes[i])
        secondPointCoords=(endingLatitudes[i], endingLongitudes[i])
        distance=geopy.distance.vincenty(firstPointCoords, secondPointCoords).miles
        trendsD.append(distance)
        speeds.append(distance/durations[i])
        selectStartingStationIDs.append(starting_station_ids[i])
print speeds
[0.000566010534311104, 0.0012732510145188824, 0.001040295567312209, 0.0016208705877544512, 0.0009005143391047667, 0.0004995060687323535, 0.0009062241015586866, 0.0014627512036821065, 0.0006121628691030777, 0.00015124867604446126, 0.0009394538887843519, 0.000850916865080783, 0.001651459334855656, 0.0006355800476895452, 0.000859586329148801, 0.0011601472326240895, 0.0009048277148934747, 0.0011354343715032932, 0.0010048871598610746, 3.9129256680186936e-05, 0.00012054104352732753, 0.0007173936111580819, 0.001307432722153699, 0.001307432722153699, 0.0014566890855060883, 0.0008248257223339261, 4.937846745601436e-05, 0.0015963653493119717, 0.0019114494478513903, 5.217556037164028e-05, 0.0010303830772131655, 0.0010709846889779822, 0.0005386620443401501, 0.00012118184020388447, 1.3038205891910393e-05, 0.0008079930665102251, 0.0021766514154320945, 0.0010261880708607781, 0.00010238648407234707, 0.001231092378084253, 0.001871769825887749, 0.001871769825887749, 0.0010577592912365266, 0.00047529003912366184, 0.0003692529804477234, 0.0003819858418424725, 0.00047077858975553075, 0.00047077858975553075, 0.0010587407323112753, 0.0007139235499785047, 0.0008977700739003681, 0.00027265914045874004, 0.00014022369815223844, 0.0019699492616381967, 0.0003761508777323963, 0.0010794489380327988, 0.0006231367138287574, 0.001553389375574806, 0.0007406566999547858, 0.0006583615110709207, 0.0014750219147242733, 0.0008771330740023083, 0.0010326165494305448, 0.00024715202769785193, 0.0015025137865819016, 0.0009851423902561215, 0.0010528696924878025, 6.875180777986147e-05, 0.0008690799275820929, 0.0013077765374722924, 0.0009927363425947168, 0.0007748056131403259, 0.001027538708013944, 0.0012591102747928212, 0.0014891045138913704, 0.0010535870819459094, 0.0011519749737262503, 0.0018124482031175808, 0.0011912836111130963, 0.0005994072824788241, 0.0004769237194823674, 0.0015772941358751862, 0.0012462734276575149, 0.0012785724256347555, 3.76974670948815e-05, 0.0013852892117253394, 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In [285]:
plt.plot(selectStartingStationIDs, speeds, "o")
plt.title("Speed at each Starting Station ID")
plt.xlabel("Starting Station ID")
plt.ylabel("Speed (miles/second)")
plt.show()

The above graph depicts the speed of each ride stemming from the at Starting Station ID for that ride. This dataset includes every ride within in the dataframe, so it is a little confusing at first. However, when the axis intervals are manipulated, trends can more easily be observed. One such trend that can also be seen in the previous graph is that there seemed to have been some sort of bike race at Starting Station ID 4000-something. Also, the speed for riders seems to be arround 0-.004 miles/second. This data can be used to infer traffic patterns, as lots of riders probably ride on the streets. Starting Stations with slower speeds stemming from them may have high traffic rates close by.

In [78]:
bikeIds=[]
for row in df["Bike ID"]:
    bikeIds.append(row)
print bikeIds
[6281.0, 6281.0, 5861.0, 5861.0, 6674.0, 6717.0, 5721.0, 5957.0, 6137.0, 6351.0, 6200.0, 6110.0, 5856.0, 6217.0, 6717.0, 6332.0, 5965.0, 6608.0, 6557.0, 6123.0, 6015.0, 6302.0, 6029.0, 5835.0, 6108.0, 6295.0, 6139.0, 6217.0, 6528.0, 6092.0, 6102.0, 6011.0, 6185.0, 6590.0, 6092.0, 5861.0, 6370.0, 5965.0, 6579.0, 6108.0, 6691.0, 5801.0, 5735.0, 5860.0, 6114.0, 6469.0, 6487.0, 6140.0, 6528.0, 6011.0, 6348.0, 6389.0, 6254.0, 5783.0, 5922.0, 6432.0, 6029.0, 6040.0, 6558.0, 5916.0, 6433.0, 6348.0, 5897.0, 6370.0, 6369.0, 6011.0, 6305.0, 6404.0, 6558.0, 6015.0, 6185.0, 5928.0, 6528.0, 5759.0, 6524.0, 6608.0, 5856.0, 5951.0, 6404.0, 6588.0, 6357.0, 6295.0, 6528.0, 5801.0, 5909.0, 6690.0, 6029.0, 5996.0, 6370.0, 6125.0, 6214.0, 6103.0, 6108.0, 6038.0, 6123.0, 5912.0, 6674.0, 6217.0, 5927.0, 6060.0, 5916.0, 5725.0, 5890.0, 5912.0, 6038.0, 6690.0, 5816.0, 6031.0, 6621.0, 6151.0, 5936.0, 6053.0, 6419.0, 5986.0, 6674.0, 6228.0, 5928.0, 6595.0, 6313.0, 6528.0, 6275.0, 5751.0, 5927.0, 6500.0, 5856.0, 6259.0, 5805.0, 5936.0, 6213.0, 6059.0, 5916.0, 6059.0, 6262.0, 5863.0, 6634.0, 5861.0, 6192.0, 5751.0, 5735.0, 5829.0, 6123.0, 5972.0, 6093.0, 6437.0, 6433.0, 6262.0, 6140.0, 6059.0, 6009.0, 5985.0, 6476.0, 5910.0, 6267.0, 6354.0, 6579.0, 6272.0, 6584.0, 6674.0, 6556.0, 6059.0, 6579.0, 6123.0, 5755.0, 6089.0, 5964.0, 6433.0, 6354.0, 5755.0, 6604.0, 5856.0, 5721.0, 6403.0, 6092.0, 6397.0, 6213.0, 6140.0, 6210.0, 6137.0, 6137.0, 6204.0, 6437.0, 6440.0, 6210.0, 5972.0, 6354.0, 6139.0, 6353.0, 6092.0, 6213.0, 5916.0, 5897.0, 5982.0, 6262.0, 6492.0, 6670.0, 6110.0, 5922.0, 6031.0, 6481.0, 5916.0, 5755.0, 6141.0, 6031.0, 6440.0, 6267.0, 6141.0, 5856.0, 5886.0, 5890.0, 6481.0, 6676.0, 6371.0, 5936.0, 6357.0, 6157.0, 6397.0, 6614.0, 5922.0, 6015.0, 5829.0, 6326.0, 6288.0, 6308.0, 5833.0, 6056.0, 6108.0, 5980.0, 6389.0, 5886.0, 5833.0, 6608.0, 6056.0, 6066.0, 6481.0, 6305.0, 6065.0, 6603.0, 5799.0, 6428.0, 6059.0, 6283.0, 5927.0, 6217.0, 5936.0, 6623.0, 6360.0, 5890.0, 6254.0, 5985.0, 5924.0, 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In [79]:
tripIds=[]
for row in df["Trip ID"]:
    tripIds.append(row)
print tripIds
[1912818, 1919661, 1933383, 1944197, 1940317, 1944075, 1944073, 1944067, 1944062, 1944063, 1944061, 1944059, 1944058, 1944054, 1944057, 1944055, 1944052, 1944050, 1944048, 1944049, 1944051, 1944046, 1944047, 1944045, 1944043, 1944042, 1981558, 1952019, 1944041, 1944039, 1944032, 1944033, 1944030, 1944025, 1947959, 1964404, 1943988, 1943982, 1943981, 1943980, 1947931, 1947930, 1947929, 1947926, 1947925, 2053757, 1947923, 1947921, 1947920, 1947919, 1947918, 1947916, 1947917, 1947915, 1947911, 1947909, 1947908, 1951931, 1951930, 1947907, 1951929, 1947906, 1951907, 1947885, 1947877, 1951896, 1951895, 1951893, 1951892, 1951891, 1951890, 1951882, 1951883, 1951880, 1955985, 1955970, 1955962, 1955953, 1955950, 1955949, 1955948, 1955941, 1955940, 1960069, 1955939, 1960067, 1960066, 1960065, 1960063, 1960062, 1960061, 1960060, 1960059, 1960058, 1960057, 1960056, 1960055, 1960054, 1960053, 1989441, 1960052, 1964229, 1964226, 1964227, 1964224, 1964223, 1964222, 1964221, 1964220, 1964219, 1964217, 1964216, 1964215, 1968441, 1964214, 1968437, 1964210, 1964209, 1964208, 1968433, 1981308, 1968432, 1968431, 1968430, 1968428, 1981302, 1968427, 1968426, 1968425, 1968424, 1968423, 1968422, 1968421, 1968420, 1972684, 1972683, 1972681, 1981289, 1972679, 1972680, 1972678, 1972676, 1972677, 1972675, 1972674, 1972673, 1972672, 1972671, 1972670, 1972669, 1972668, 1972667, 1972666, 1976951, 1976950, 1972662, 1976948, 1976947, 1976945, 1976946, 1976944, 1976943, 1976942, 1976941, 1976940, 1976939, 1981257, 1981256, 1989358, 1981255, 1981254, 1981253, 1981252, 1981250, 1981249, 1981248, 1981246, 1981245, 1989345, 1981243, 1981242, 1981241, 1985572, 1985570, 1985571, 1985569, 1985568, 1985567, 1985566, 1989333, 1989332, 1989331, 1989330, 1989329, 1989328, 1993100, 1996874, 1996873, 2004423, 2015755, 2015754, 2015753, 2015752, 2019548, 2019547, 2031376, 2019546, 2019545, 2019544, 2019543, 2019542, 2019541, 2019540, 2019539, 2019538, 2023379, 2023376, 2023374, 2023371, 2023369, 2023368, 2023367, 2023366, 2023364, 2027285, 2023335, 2023334, 2027261, 2027260, 2027258, 2027252, 2027236, 2027235, 2027233, 2027221, 2027211, 2031266, 2031264, 2031265, 2031259, 2031251, 2048686, 2031247, 2031246, 2035438, 2031244, 2031243, 2031242, 2031241, 2035394, 2031203, 2031202, 2031181, 2035370, 2031180, 2035368, 2035366, 2035364, 2035362, 2035363, 2035361, 2035359, 2035360, 2035358, 2035350, 2035345, 2035342, 2035341, 2035340, 2035338, 2035337, 2035334, 2035333, 2035332, 2039635, 2039634, 2035330, 2035331, 2035329, 2035328, 2035327, 2035317, 2035311, 2035287, 2035282, 2035280, 2035274, 2039573, 2039566, 2039561, 2039563, 2039547, 2039549, 2039544, 2039545, 2039542, 2039543, 2039539, 2039536, 2039537, 2039538, 2039535, 2039518, 2043907, 2039497, 2039496, 2039495, 2039492, 2039476, 2039475, 2043876, 2043875, 2043874, 2043872, 2043848, 2043846, 2043842, 2043830, 2043811, 2043805, 2043800, 2043801, 2043799, 2043798, 2043797, 2043796, 2043795, 2043794, 2043789, 2043791, 2043790, 2043788, 2048320, 2048318, 2043785, 2048317, 2048315, 2048316, 2048307, 2048303, 2048308, 2048283, 2048278, 2048276, 2048261, 2048258, 2048260, 2048256, 2048257, 2048249, 2048229, 2048227, 2048223, 2048201, 2048199, 2048200, 2048196, 2052846, 2057605, 2057604, 2052840, 2052842, 2052829, 2052796, 2072094, 2052793, 2052782, 2052746, 2052739, 2052738, 2052736, 2052734, 2052735, 2057487, 2057488, 2057486, 2072026, 2057484, 2057483, 2057481, 2057480, 2057482, 2057474, 2057477, 2057467, 2057450, 2057447, 2057448, 2057443, 2057442, 2057412, 2057411, 2057410, 2057408, 2057407, 2057406, 2057405, 2057404, 2062208, 2062205, 2062203, 2062204, 2062202, 2062201, 2067041, 2062200, 2062199, 2062198, 2062197, 2062195, 2062196, 2062194, 2062193, 2062192, 2062191, 2062190, 2062189, 2062188, 2067025, 2067024, 2062187, 2062186, 2067021, 2062184, 2062183, 2067020, 2062182, 2067015, 2067014, 2090422, 2062181, 2067012, 2067011, 2067009, 2067010, 2071902, 2067008, 2067007, 2067006, 2067005, 2067004, 2067002, 2067003, 2067000, 2067001, 2066999, 2066998, 2066997, 2066996, 2066994, 2066993, 2066992, 2066991, 2066990, 2071881, 2071882, 2066989, 2071879, 2071878, 2071877, 2071876, 2071871, 2071872, 2071873, 2071874, 2071875, 2071870, 2071869, 2071868, 2071867, 2071866, 2071865, 2071864, 2071863, 2071861, 2071859, 2071860, 2071858, 2071857, 2071856, 2071855, 2071854, 2071853, 2071852, 2076774, 2076775, 2076773, 2076772, 2076771, 2076770, 2076769, 2076768, 2076767, 2076766, 2076764, 2076762, 2076763, 2076761, 2076760, 2076758, 2076756, 2076755, 2081693, 2081692, 2081691, 2081688, 2081690, 2076748, 2081687, 2081686, 2081685, 2081684, 2081683, 2081682, 2081679, 2081678, 2081677, 2081676, 2081675, 2081674, 2081673, 2081672, 2086624, 2086623, 2086622, 2086621, 2086619, 2086620, 2086618, 2086617, 2090308, 2090307, 2090306, 2090305, 2090304, 2090303, 2093999, 2093998, 2093997, 2093996, 2097696, 2097697, 2097695, 2097694, 2097693, 2101402, 2101401, 2101400, 2101399, 2101398, 2101397, 2116366, 2112531, 2112530, 2112529, 2112528, 2112527, 2116360, 2116332, 2116315, 2116289, 2120296, 2120275, 2120246, 2120245, 2120191, 2120122, 2120127, 2124355, 2124354, 2120103, 2124350, 2124342, 2124267, 2128632, 2124238, 2124233, 2124187, 2124188, 2124146, 2128530, 2128457, 2128453, 2128450, 2128416, 2128417, 2128388, 2128379, 2128360, 2128359, 2128358, 2128357, 2128356, 2133003, 2128338, 2132979, 2132976, 2132977, 2132974, 2132971, 2132968, 2137851, 2159507, 2132906, 2132896, 2132885, 2132884, 2132877, 2132868, 2132863, 2132860, 2132855, 2137731, 2137706, 2132824, 2132812, 2132787, 2132785, 2132763, 2132742, 2137617, 2137616, 2147948, 2137557, 2137549, 2142592, 2142590, 2142587, 2137527, 2137508, 2137504, 2137468, 2137466, 2137464, 2137455, 2137446, 2137444, 2137436, 2137435, 2137429, 2137428, 2137402, 2142423, 2142400, 2142392, 2142390, 2142387, 2142385, 2142383, 2142384, 2142378, 2142380, 2142379, 2142377, 2142370, 2147690, 2142350, 2147682, 2142349, 2142348, 2142347, 2142345, 2142346, 2142341, 2142337, 2142336, 2142320, 2142314, 2142316, 2142318, 2147639, 2147629, 2147598, 2147594, 2147595, 2147591, 2147561, 2147547, 2147543, 2147514, 2147515, 2147473, 2147457, 2147458, 2147450, 2147434, 2147422, 2147426, 2147411, 2147414, 2147410, 2147409, 2147408, 2147407, 2152913, 2147406, 2147405, 2147404, 2147403, 2147401, 2147402, 2147400, 2147399, 2147381, 2147374, 2147373, 2152868, 2152858, 2152850, 2152853, 2152851, 2152841, 2152840, 2158625, 2152811, 2152809, 2152800, 2176925, 2152790, 2152791, 2158586, 2152788, 2152786, 2170589, 2152764, 2152767, 2152763, 2170577, 2152762, 2158558, 2152760, 2152748, 2152747, 2152724, 2152713, 2152710, 2152704, 2152697, 2152696, 2152694, 2158488, 2152692, 2152693, 2152689, 2158481, 2152686, 2152687, 2158478, 2158476, 2158477, 2158467, 2158445, 2158443, 2158442, 2158440, 2158438, 2158439, 2158437, 2158429, 2158421, 2158417, 2158416, 2158408, 2158407, 2158409, 2158406, 2158405, 2158393, 2158391, 2158381, 2158371, 2158349, 2158345, 2158346, 2158342, 2158347, 2158339, 2158334, 2158332, 2158302, 2158284, 2158288, 2158281, 2158280, 2158282, 2158278, 2158276, 2164225, 2158270, 2164201, 2158245, 2158232, 2164181, 2164170, 2158222, 2170238, 2164169, 2158216, 2164158, 2164140, 2158186, 2164130, 2164132, 2164122, 2164121, 2287674, 2164054, 2164052, 2164053, 2164050, 2164049, 2164046, 2164047, 2164045, 2164044, 2164043, 2164042, 2164041, 2164039, 2164040, 2164027, 2164033, 2164020, 2170081, 2170080, 2170062, 2176364, 2164004, 2163997, 2170056, 2170051, 2170050, 2170049, 2163989, 2170025, 2170015, 2170006, 2170005, 2170004, 2170003, 2170001, 2170000, 2169999, 2169994, 2169959, 2169934, 2169933, 2176234, 2169931, 2169932, 2169930, 2169929, 2169928, 2169926, 2169925, 2176223, 2176221, 2176222, 2169924, 2176219, 2176218, 2176215, 2176216, 2169923, 2169922, 2176217, 2176214, 2176211, 2176202, 2176201, 2182651, 2176181, 2176176, 2182612, 2182594, 2176138, 2176136, 2176137, 2182588, 2176114, 2182516, 2176068, 2176067, 2176065, 2176066, 2182497, 2182493, 2182437, 2182435, 2182436, 2182434, 2182432, 2182395, 2182394, 2182393, 2363847, 2182391, 2182392, 2182379, 2182354, 2182353, 2182358, 2182345, 2182344, 2182326, 2182327, 2182307, 2182305, 2188783, 2182304, 2182303, 2182301, 2188778, 2188776, 2188777, 2188775, 2195265, 2188774, 2188773, 2188772, 2188771, 2188770, 2188768, 2188767, 2188765, 2188766, 2188764, 2188763, 2188762, 2208263, 2195251, 2188760, 2188759, 2195248, 2195247, 2208256, 2195246, 2195245, 2195244, 2195243, 2195242, 2195241, 2195240, 2208248, 2208247, 2195239, 2195238, 2201735, 2201736, 2201734, 2201732, 2201733, 2208238, 2201731, 2208236, 2208235, 2208232, 2208230, 2208231, 2208229, 2293800, 2214746, 2214745, 2214744, 2214743, 2227780, 2247343, 2247342, 2247341, 2247340, 2253865, 2260401, 2260400, 2266949, 2266943, 2266931, 2273530, 2273532, 2266930, 2266928, 2273527, 2273526, 2273525, 2280191, 2273524, 2273523, 2293747, 2286906, 2273509, 2273508, 2273507, 2280172, 2280165, 2280164, 2280163, 2273499, 2273500, 2273498, 2280148, 2286870, 2280146, 2280145, 2280140, 2280133, 2280131, 2280130, 2280129, 2280128, 2280125, 2280123, 2280124, 2280120, 2280118, 2280114, 2280112, 2280106, 2280107, 2280104, 2286820, 2286819, 2286811, 2286809, 2286808, 2286810, 2286801, 2286799, 2286790, 2286789, 2286784, 2286782, 2286781, 2286783, 2286780, 2286779, 2286778, 2286777, 2286776, 2286771, 2286770, 2286767, 2286766, 2286765, 2293595, 2293591, 2286760, 2286759, 2293588, 2286758, 2293586, 2293584, 2293585, 2293583, 2293581, 2293582, 2293580, 2293579, 2293577, 2293574, 2293568, 2293563, 2293556, 2293553, 2293550, 2293551, 2293538, 2293536, 2293513, 2293510, 2293507, 2293504, 2293503, 2293502, 2293499, 2293497, 2293498, 2293495, 2293496, 2300367, 2293493, 2300365, 2300364, 2300363, 2657183, 2293485, 2300353, 2300352, 2300349, 2300347, 2300346, 2300339, 2300333, 2300332, 2300331, 2300330, 2300329, 2321132, 2300328, 2300327, 2300326, 2300325, 2300324, 2307230, 2307229, 2300323, 2307227, 2300322, 2300321, 2300319, 2300320, 2307222, 2307221, 2307220, 2307218, 2307219, 2307217, 2307216, 2307215, 2307213, 2307214, 2307211, 2307212, 2307210, 2307209, 2307208, 2307207, 2307206, 2314140, 2307205, 2307204, 2307203, 2307202, 2307201, 2307200, 2307199, 2307198, 2307197, 2307196, 2307195, 2335086, 2307193, 2314125, 2314126, 2314123, 2314124, 2314122, 2314121, 2314120, 2314119, 2314117, 2314118, 2314116, 2314115, 2314113, 2314114, 2314112, 2314111, 2314110, 2314109, 2314108, 2314107, 2314105, 2314104, 2314103, 2314101, 2314100, 2314102, 2321059, 2321058, 2321053, 2321057, 2321055, 2321054, 2321056, 2321052, 2321051, 2321050, 2321049, 2321047, 2321044, 2321045, 2321043, 2321042, 2321041, 2321040, 2321039, 2321038, 2321037, 2608358, 2321036, 2328020, 2321035, 2328018, 2328017, 2328016, 2328015, 2328014, 2328013, 2328011, 2328012, 2328010, 2328009, 2328008, 2328007, 2328006, 2328005, 2335017, 2328004, 2328003, 2328002, 2328001, 2328000, 2327999, 2327998, 2335007, 2335006, 2335004, 2335003, 2335001, 2335000, 2334998, 2334997, 2334996, 2334994, 2334995, 2370299, 2334989, 2334987, 2334984, 2342016, 2334981, 2334982, 2342011, 2342012, 2342010, 2342009, 2342008, 2342006, 2342007, 2342005, 2342003, 2342004, 2342001, 2342002, 2342000, 2341999, 2341998, 2341997, 2349046, 2349045, 2349044, 2349043, 2349042, 2341996, 2341995, 2349038, 2349039, 2349037, 2349036, 2349035, 2349034, 2349033, 2349032, 2349031, 2349030, 2349028, 2349029, 2356091, 2356092, 2356089, 2356090, 2356088, 2356087, 2356086, 2356085, 2356084, 2356083, 2356082, 2356081, 2356080, 2356079, 2363151, 2363150, 2356078, 2363148, 2363147, 2363145, 2363146, 2363144, 2363143, 2370226, 2370224, 2370225, 2370223, 2370222, 2370221, 2370220, 2370219, 2370218, 2370217, 2377302, 2391475, 2391474, 2412745, 2412744, 2412743, 2412738, 2419849, 2419847, 2419846, 2419845, 2419844, 2419842, 2419841, 2419840, 2419839, 2419838, 2419837, 2426979, 2463333, 2426977, 2419835, 2426975, 2426972, 2426970, 2426969, 2426968, 2426967, 2426966, 2426965, 2426964, 2426963, 2426962, 2426960, 2426959, 2426958, 2426957, 2426956, 2434141, 2434140, 2434139, 2434138, 2434136, 2434135, 2434134, 2434133, 2434111, 2434110, 2434104, 2441312, 2441311, 2441308, 2441307, 2441306, 2441305, 2441304, 2441303, 2441301, 2441300, 2441299, 2448543, 2441298, 2441297, 2448534, 2448532, 2448531, 2448529, 2448528, 2448527, 2448526, 2448525, 2448524, 2448523, 2448522, 2455837, 2455835, 2455836, 2455834, 2455833, 2455832, 2455831, 2455829, 2455828, 2455827, 2455826, 2455825, 2455824, 2463182, 2455822, 2463181, 2455818, 2455813, 2463172, 2455805, 2455804, 2455803, 2455798, 2463154, 2455797, 2455792, 2455791, 2455790, 2463144, 2455787, 2455784, 2463139, 2463136, 2463130, 2463129, 2463126, 2463127, 2463125, 2463124, 2463123, 2463122, 2463120, 2463117, 2463119, 2463118, 2463116, 2463114, 2463115, 2463112, 2463111, 2463110, 2463109, 2463108, 2463107, 2463105, 2463104, 2463103, 2463102, 2470501, 2470503, 2470499, 2470497, 2470493, 2470492, 2470491, 2470490, 2470486, 2470487, 2470484, 2470485, 2470482, 2470483, 2470478, 2470479, 2470480, 2470477, 2470476, 2470475, 2615650, 2470473, 2470474, 2470471, 2470472, 2470470, 2470467, 2470461, 2470459, 2470458, 2470457, 2477926, 2492936, 2477924, 2477923, 2477922, 2477921, 2477920, 2477919, 2477918, 2485372, 2485371, 2477880, 2485369, 2485368, 2485363, 2485362, 2485361, 2485360, 2485358, 2485359, 2485357, 2492875, 2485356, 2492872, 2485354, 2492870, 2492869, 2492868, 2492865, 2508380, 2492864, 2500529, 2492863, 2492862, 2492861, 2492860, 2492859, 2631477, 2492856, 2492857, 2492855, 2492852, 2492850, 2492851, 2492849, 2492848, 2500512, 2492847, 2492846, 2500507, 2492844, 2500506, 2500505, 2500504, 2500502, 2500503, 2500501, 2500500, 2500498, 2500499, 2500497, 2500496, 2500495, 2500494, 2500488, 2500485, 2500466, 2500447, 2500448, 2500446, 2500445, 2500444, 2500443, 2500442, 2500441, 2500431, 2508257, 2500409, 2500406, 2500405, 2500404, 2500403, 2508235, 2508234, 2508208, 2508194, 2508193, 2508187, 2508184, 2508189, 2508142, 2508134, 2508119, 2508116, 2508118, 2508117, 2508115, 2508114, 2508111, 2508110, 2508113, 2508109, 2508108, 2508097, 2508087, 2516067, 2508086, 2516043, 2516042, 2516023, 2516012, 2516015, 2516009, 2516000, 2515992, 2515990, 2515991, 2515989, 2515988, 2515980, 2515959, 2515944, 2515946, 2515930, 2515931, 2515927, 2515928, 2515923, 2515925, 2515924, 2515922, 2515907, 2515902, 2515892, 2515891, 2515889, 2515890, 2523890, 2523887, 2523886, 2515886, 2515885, 2523882, 2523881, 2523880, 2523879, 2523878, 2523875, 2523874, 2523876, 2523877, 2523873, 2523872, 2523870, 2523871, 2523869, 2523868, 2523867, 2531877, 2523866, 2523865, 2531874, 2531873, 2531872, 2531871, 2531870, 2531869, 2531868, 2531867, 2539881, 2539880, 2539879, 2539878, 2547349, 2547350, 2547348, 2547347, 2547346, 2547345, 2547344, 2547343, 2554817, 2554816, 2562293, 2562292, 2562291, 2569770, 2569769, 2592213, 2592212, 2592211, 2592210, 2592209, 2599727, 2599726, 2599714, 2622898, 2599711, 2599710, 2599709, 2599708, 2599707, 2599706, 2599705, 2599704, 2599702, 2599701, 2607251, 2599697, 2607248, 2599694, 2607246, 2607245, 2607244, 2607242, 2607241, 2607240, 2607237, 2607234, 2607233, 2607231, 2607232, 2607229, 2607230, 2607226, 2607225, 2607223, 2607224, 2607222, 2607219, 2607220, 2607218, 2607217, 2607216, 2607215, 2607214, 2614944, 2614943, 2614942, 2614941, 2614940, 2614923, 2614919, 2614925, 2614898, 2614896, 2614888, 2614887, 2614884, 2614881, 2614880, 2614856, 2614851, 2614850, 2614848, 2614847, 2614844, 2614814, 2614813, 2614812, 2614808, 2614781, 2622657, 2622655, 2622653, 2622652, 2622651, 2622629, 2622622, 2622621, 2622582, 2622581, 2622579, 2622578, 2622576, 2622565, 2622551, 2622547, 2622546, 2622545, 2622543, 2622542, 2630577, 2630578, 2630545, 2630542, 2630543, 2630541, 2630540, 2630536, 2630514, 2630513, 2630503, 2630483, 2630481, 2638627, 2630477, 2630475, 2630473, 2630470, 2630472, 2630462, 2630463, 2630461, 2630460, 2630457, 2630459, 2638596, 2630441, 2638595, 2630432, 2630425, 2630434, 2638576, 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23631296, 23631295, 23631292, 23631293, 23631291, 23631290, 23631289, 23631288, 23631287, 23631286, 23639663, 23631285, 23639662, 23635442, 23631284, 23639660, 23635439, 23631283, 23635437, 23631282, 23635436, 23635435, 23635434, 23635433, 23635431, 23635430, 23635429, 23635428, 23635427, 23635426, 23635425, 23635424, 23635423, 23635422, 23635420, 23635421, 23635419, 23635418, 23635417, 23635416, 23635414, 23635415, 23635413, 23639630, 23639629, 23635412, 23635411, 23635410, 23635409, 23635408, 23639622, 23635407, 23635406, 23635405, 23635404, 23639618, 23635403, 23639616, 23639615, 23639614, 23639612, 23639613, 23639611, 23639609, 23639610, 23639608, 23639607, 23643865, 23639606, 23639605, 23639604, 23639603, 23639602, 23639601, 23639600, 23639599, 23639598, 23639596, 23639597, 23639595, 23639594, 23639593, 23639592, 23639591, 23639590, 23639589, 23639587, 23639588, 23652454, 23639585, 23639586, 23639584, 23652450, 23639583, 23639582, 23639581, 23639579, 23639578, 23639575, 23639572, 23639570, 23639567, 23643824, 23643823, 23639566, 23643821, 23664959, 23643820, 23639565, 23661118, 23639564, 23643817, 23639563, 23643816, 23643814, 23643813, 23643811, 23643812, 23643810, 23643809, 23643808, 23643807, 23643806, 23643801, 23643796, 23643795, 23643794, 23643792, 23643793, 23643791, 23648078, 23643790, 23643789, 23656732, 23643788, 23643787, 23643786, 23643785, 23643784, 23648069, 23648068, 23648067, 23648066, 23648065, 23648064, 23648063, 23648062, 23648060, 23648061, 23648059, 23648058, 23648057, 23648056, 23648055, 23648053, 23648054, 23648052, 23652372, 23648051, 23652371, 23652367, 23648050, 23652369, 23648049, 23652365, 23648048, 23648047, 23648046, 23715783, 23648045, 23648044, 23652359, 23652358, 23652357, 23711694, 23652356, 23648043, 23652354, 23794218, 23652353, 23652347, 23652340, 23652339, 23652341, 23652338, 23652337, 23652335, 23652334, 23652333, 23652331, 23652332, 23656666, 23656665, 23656664, 23652330, 23656662, 23656661, 23656660, 23656659, 23656658, 23656657, 23656656, 23661008, 23656655, 23656654, 23661005, 23656653, 23664842, 23664841, 23732455, 23741000, 23661002, 23661003, 23661001, 23661000, 23660999, 23660998, 23660997, 23660996, 23660995, 23660994, 23660993, 23660992, 23660991, 23660990, 23664826]
In [197]:
import math
selectBikeIds=[]
selectTripIds=[]
for i in range(len(df)):
        if math.isnan(startingLatitudes[i])==True or math.isnan(startingLongitudes[i])==True or math.isnan(endingLatitudes[i])==True or math.isnan(endingLongitudes[i])==True or startingLatitudes[i]==0.0 or startingLongitudes[i]==0.0 or endingLatitudes[i]==0.0 or endingLongitudes[i]==0.0:
            selectBikeIds.append(bikeIds[i])
            selectTripIds.append(tripIds[i])
print selectBikeIds, selectTripIds
[6065.0, 6286.0, 6054.0, 6054.0, 6054.0, 6054.0, 6092.0, 6092.0, 5984.0, 6194.0, 6427.0, 5791.0, 5922.0, 6122.0, 6405.0, 6613.0, 6390.0, 6028.0, 6581.0, 6400.0, 6085.0, 6436.0, 6289.0, 5824.0, 6240.0, 5824.0, 6442.0, 6442.0, 6518.0, 6439.0, 5926.0, 6024.0, 6067.0, 6253.0, 5926.0, 6273.0, 6024.0, 6041.0, 6041.0, 5961.0, 5926.0, 6616.0, 6511.0, 5751.0, 6649.0, 6247.0, 6065.0, 6065.0, 5893.0, 5893.0, 5893.0, 6379.0, 6029.0, 6237.0, 6234.0, 6682.0, 6432.0, 6432.0, 6146.0, 5929.0, 5838.0, 6197.0, 5830.0, 5808.0, 5931.0, 6296.0, 6649.0, 6101.0, 5949.0, 6527.0, 5976.0, 6206.0, 5908.0, 5832.0, 5862.0, 6103.0, 6146.0, 5910.0, 6566.0, 5847.0, 5974.0, 6273.0, 6320.0, 5974.0, 6203.0, 6181.0, 6397.0, 5863.0, 6032.0, 6496.0, 6422.0, 6220.0, 5780.0, 6328.0, 5863.0, 6047.0, 6677.0, 6437.0, 5836.0, 6084.0, 6479.0, 6084.0, 6679.0, 6437.0, 6167.0, 6626.0, 6626.0, 6603.0, 6470.0, 6545.0, 6547.0, 6604.0, 6645.0, 6603.0, 5891.0, 6403.0, 5933.0, 6429.0, 6407.0, 6476.0, 6028.0, 6003.0, 6686.0, 6269.0, 5901.0, 6015.0, 5900.0, 5788.0, 6369.0, 6621.0, 5949.0, 6619.0, 5780.0, 6494.0, 6313.0, 6245.0, 5830.0, 6491.0, 6413.0, 6162.0, 6284.0, 6282.0, 6411.0, 6057.0, 6269.0, 6207.0, 5977.0, 6250.0, 6461.0, 6441.0, 6188.0, 6291.0, 5972.0, 6017.0, 5966.0, 6078.0, 6017.0, 5755.0, 6067.0, 6294.0, 6623.0, 5966.0, 6510.0, 5832.0, 6183.0, 6279.0, 6461.0, 6038.0, 5856.0, 5958.0, 5788.0, 5958.0, 6291.0, 5914.0, 6008.0, 5992.0, 6008.0, 6307.0, 6319.0, 6654.0, 6431.0, 6045.0, 6139.0, 5863.0, 6326.0, 6635.0, 5987.0, 6332.0, 5784.0, 6217.0, 6545.0, 5936.0, 6238.0, 6625.0, 5847.0, 6251.0, 5881.0, 6277.0, 5829.0, 5974.0, 6476.0, 6451.0, 6363.0, 5847.0, 6062.0, 5733.0, 6218.0, 6616.0, 5778.0, 5974.0, 5848.0, 6101.0, 6437.0, 5770.0, 5999.0, 5977.0, 5824.0, 5816.0, 5997.0, 5974.0, 6610.0, 6025.0, 6032.0, 6244.0, 6005.0, 5838.0, 6527.0, 5974.0, 5764.0, 5999.0, 5957.0, 6547.0, 6019.0, 6654.0, nan, 6308.0, 6639.0, 6002.0, 5967.0, 5908.0, 6151.0, 5992.0, 5936.0, 5806.0, 6242.0, 6527.0, 6139.0, 5830.0, 6097.0, 6089.0, 6439.0, 6076.0, 5985.0, 5980.0, 5997.0, 6032.0, 5949.0, 6120.0, 6035.0, 6185.0, 6376.0, 6008.0, 6171.0, 6215.0, 5770.0, 5879.0, 5788.0, 6279.0, 5939.0, 6491.0, 6463.0, 5826.0, 6422.0, 6473.0, 6440.0, 5751.0, 6439.0, 5788.0, 6267.0, 5932.0, 5850.0, 6635.0, 6026.0, 6671.0, 5931.0, 6621.0, 6275.0, 5991.0, 5919.0, 5772.0, 6351.0, 6441.0, 5726.0, 5889.0, 5771.0, 5857.0, 5915.0, 6138.0, 6411.0, 6671.0, 5835.0, 6163.0, 5974.0, 5992.0, 5949.0, 6256.0, 6523.0, 5791.0, 5822.0, 6291.0, 5990.0, 6548.0, 5785.0, 6549.0, 5858.0, 6057.0, 6203.0, 6655.0, 5929.0, 6496.0, 5992.0, 6292.0, 6533.0, 5772.0, 6580.0, 6331.0, 5999.0, 6058.0, 6291.0, 5827.0, 6494.0, 6431.0, 6686.0, 5726.0, 6010.0, 6654.0, 6436.0, 5987.0, 5972.0, 5918.0, 6322.0, 6316.0, 5905.0, 5988.0, 6393.0, 6575.0, 6482.0, 5816.0, 6045.0, 6678.0, 6655.0, 5949.0, 6683.0, 6469.0, 6531.0, 6462.0, 5839.0, 6200.0, 6136.0, 6302.0, 5961.0, 6059.0, 5971.0, 6681.0, 5725.0, 6249.0, 6681.0, 5990.0, 6153.0, 5909.0, 5952.0, 6162.0, 6085.0, 5910.0, 6500.0, 6380.0, 5999.0, 5838.0, 6649.0, 5817.0, 5875.0, 5875.0, 6107.0, 6434.0, 6101.0, 6525.0, 6654.0, 5832.0, 5976.0, 6178.0, 5999.0, 6269.0, 6292.0, 6457.0, 6067.0, 6680.0, 6084.0, 6200.0, 6095.0, 6157.0, 6163.0, 6685.0, 6223.0, 6066.0, 6025.0, 5758.0, 6110.0, 6680.0, 6180.0, 6062.0, 5754.0, 6397.0, 6660.0, 6221.0, 5855.0, 6249.0, 6043.0, 6633.0, 5919.0, 5988.0, 5820.0, 6292.0, 6209.0, 6691.0, 6654.0, 6010.0, 6553.0, 6150.0, 6076.0, 6608.0, 6491.0, 5910.0, 6066.0, 6049.0, 5743.0, 6478.0, 6092.0, 5951.0, 5845.0, 6728.0, 6480.0, 6141.0, 6334.0, 6611.0, 6683.0, 5804.0, 6644.0, 6183.0, 6135.0, 6183.0, 6644.0, 6135.0, 5886.0, 6026.0, 6400.0, 5948.0, 5957.0, 6073.0, 6240.0, 6132.0, 5926.0, 6245.0, 6047.0, 6269.0, 6681.0, 6287.0, 5993.0, 5987.0, 5829.0, 6206.0, 6397.0, 6424.0, 6587.0, 6095.0, 6062.0, 6654.0, 6381.0, 5737.0, 5845.0, 6237.0, 5910.0, 6167.0, 5905.0, 6576.0, 6706.0, 5969.0, 6293.0, 5940.0, 6595.0, 5772.0, 6527.0, 6017.0, 6553.0, 6058.0, 5957.0, 6288.0, 5735.0, 6437.0, 6039.0, 6649.0, 6176.0, 5847.0, 6078.0, 5900.0, 6479.0, 6215.0, 6281.0, 6274.0, 6536.0, 6479.0, 6544.0, 6179.0, 5814.0, 6523.0, 5885.0, 6066.0, 6010.0, 6258.0, 5867.0, 6244.0, 5875.0, 5909.0, 5871.0, 6683.0, 6380.0, 5872.0, 6173.0, 5912.0, 5845.0, 5990.0, 5851.0, 6109.0, 6185.0, 6275.0, 6223.0, 6429.0, 6407.0, 6466.0, 5801.0, 5846.0, 6313.0, 6275.0, 5925.0, 5993.0, 5762.0, 6625.0, 6658.0, 6207.0, 6049.0, 5784.0, 6599.0, 6650.0, 6677.0, 6206.0, 5974.0, 5809.0, 5904.0, 5791.0, 6254.0, 6344.0, 5830.0, 6365.0, 6059.0, 5811.0, 6509.0, 6503.0, 6496.0, 6146.0, 5826.0, 6238.0, 6636.0, 6479.0, 6289.0, 5777.0, 6120.0, 6274.0, 6024.0, 5833.0, 6644.0, 6095.0, 6671.0, 5997.0, 5966.0, 6658.0, 6401.0, 6473.0, 5914.0, 6017.0, 6381.0, 6423.0, 5722.0, 6491.0, 6457.0, 5830.0, 5778.0, 5738.0, 6295.0, 5809.0, 5770.0, 6142.0, 5801.0, 6406.0, 6564.0, 6660.0, 6055.0, 6033.0, 6042.0, 5952.0, 6692.0, 6644.0, 6389.0, 5964.0, 5833.0, 6463.0, 6646.0, 6655.0, 6334.0, 6315.0, 5985.0, 5830.0, 6129.0, 6521.0, 5941.0, 6727.0, 6024.0, 5735.0, 6009.0, 6095.0, 6500.0, 6142.0, 6212.0, 6150.0, 6401.0, 5987.0, 6310.0, 5999.0, 6248.0, 5852.0, 6524.0, 5965.0, 6074.0, 6551.0, 6258.0, 6579.0, 6059.0, 5987.0, 6025.0, 6133.0, 6371.0, 5998.0, 5873.0, 6313.0, 5830.0, 6400.0, 5807.0, 6685.0, 6137.0, 5754.0, 6571.0, 5971.0, 6204.0, 6021.0, 6357.0, 6654.0, 6018.0, 5770.0, 6246.0, 5753.0, 5932.0, 5924.0, 6101.0, 5944.0, 6639.0, 5756.0, 5855.0, 6256.0, 6055.0, 6370.0, 6101.0, 6635.0, 6082.0, 6367.0, 6220.0, 6613.0, 6677.0, 6168.0, 6032.0, 6188.0, 6623.0, 5782.0, 6120.0, 5809.0, 6155.0, 6678.0, 5757.0, 6524.0, 5829.0, 6492.0, 5986.0, 5838.0, 6410.0, 6585.0, 6497.0, 5741.0, 6403.0, 5832.0, 6645.0, 5908.0, 5801.0, 6384.0, 6615.0, 6478.0, 6400.0, 6314.0, 5923.0, 5886.0, 6687.0, 6595.0, 5872.0, 6199.0, 6213.0, 6681.0, 5867.0, 6496.0, 6389.0, 6047.0, 6572.0, 5737.0, 5821.0, 6411.0, 5875.0, 6536.0, 6199.0, 6038.0, 6683.0, 5972.0, 6107.0, 6021.0, 6619.0, 5867.0, 5826.0, 5958.0, 6406.0, 6238.0, 5973.0, 6021.0, 5941.0, 5992.0, 6494.0, 5973.0, 6327.0, 6288.0, 6441.0, 6174.0, 6676.0, 6240.0, 6315.0, 6411.0, 6564.0, 6545.0, 6390.0, 5826.0, 6308.0, 6576.0, 6347.0, 6236.0, 5982.0, 6214.0, 6611.0, 6581.0, 6547.0, 6635.0, 5901.0, 6711.0, 6101.0, 5844.0, 6549.0, 5766.0, 6009.0, 6014.0, 6139.0, 6478.0, 6088.0, 6046.0, 5900.0, 6426.0, 6244.0, 6242.0, 6095.0, 6174.0, 5999.0, 6009.0, 5796.0, 6242.0, 6400.0, 6417.0, 6101.0, 6183.0, 6014.0, 6098.0, 5770.0, 5863.0, 6213.0, 6654.0, 6227.0, 6360.0, 6074.0, 6500.0, 6492.0, 6515.0, 6284.0, 6613.0, 5901.0, 6654.0, 6446.0, 6209.0, 6104.0, 6558.0, 6683.0, 6357.0, 5860.0, 5842.0, 6649.0, 6220.0, 6307.0, 6060.0, 6120.0, 6621.0, 6098.0, 5771.0, 5912.0, 5981.0, 6440.0, 6009.0, 5796.0, 6367.0, 5931.0, 6061.0, 6312.0, 5756.0, 6692.0, 5830.0, 6619.0, 6386.0, 5841.0, 6224.0, 6109.0, 5993.0, 6162.0, 6306.0, 5879.0, 6523.0, 6018.0, 6622.0, 5859.0, 5958.0, 6619.0, 5932.0, 5925.0, 5715.0, 6449.0, 6469.0, 6285.0, 6178.0, 6134.0, 5830.0, 6239.0, 6478.0, 6523.0, 6491.0, 6473.0, 6454.0, 6411.0, 6315.0, 5936.0, 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In [82]:
plt.plot(selectTripIds, selectBikeIds, 'o')
plt.title("Trips that contained missing or invalid coordinate values (Bike ID number attached to Trip Number)")
plt.xlabel("Trip ID")
plt.ylabel("Bike ID")
plt.show()

I chose to create this graph because when performing calculations throughout the coding challenge, I was intrigued by the missing coordinate values and empty cells in the excel spreadsheet. Maybe this graph will lead to some insight as to which bikes did not yield sufficient location data, and for which trips.

In [287]:
import pandas as pd
df=pd.read_csv("metro-bike-share-trip-data.csv", parse_dates=["Start Time"], index_col="Start Time")
df
Out[287]:
Trip ID Duration End Time Starting Station ID Starting Station Latitude Starting Station Longitude Ending Station ID Ending Station Latitude Ending Station Longitude Bike ID Plan Duration Trip Route Category Passholder Type Starting Lat-Long Ending Lat-Long
Start Time
2016-07-07 04:17:00 1912818 180 2016-07-07T04:20:00 3014.0 34.056610 -118.237210 3014.0 34.056610 -118.237210 6281.0 30.0 Round Trip Monthly Pass {'longitude': '-118.23721', 'latitude': '34.05... {'longitude': '-118.23721', 'latitude': '34.05...
2016-07-07 06:00:00 1919661 1980 2016-07-07T06:33:00 3014.0 34.056610 -118.237210 3014.0 34.056610 -118.237210 6281.0 30.0 Round Trip Monthly Pass {'longitude': '-118.23721', 'latitude': '34.05... {'longitude': '-118.23721', 'latitude': '34.05...
2016-07-07 10:32:00 1933383 300 2016-07-07T10:37:00 3016.0 34.052898 -118.241560 3016.0 34.052898 -118.241560 5861.0 365.0 Round Trip Flex Pass {'longitude': '-118.24156', 'latitude': '34.05... {'longitude': '-118.24156', 'latitude': '34.05...
2016-07-07 10:37:00 1944197 10860 2016-07-07T13:38:00 3016.0 34.052898 -118.241560 3016.0 34.052898 -118.241560 5861.0 365.0 Round Trip Flex Pass {'longitude': '-118.24156', 'latitude': '34.05... {'longitude': '-118.24156', 'latitude': '34.05...
2016-07-07 12:51:00 1940317 420 2016-07-07T12:58:00 3032.0 34.049889 -118.255880 3032.0 34.049889 -118.255880 6674.0 0.0 Round Trip Walk-up {'longitude': '-118.25588', 'latitude': '34.04... {'longitude': '-118.25588', 'latitude': '34.04...
2016-07-07 12:51:00 1944075 780 2016-07-07T13:04:00 3021.0 34.045609 -118.237030 3054.0 34.039219 -118.236490 6717.0 30.0 One Way Monthly Pass {'longitude': '-118.23703', 'latitude': '34.04... {'longitude': '-118.23649', 'latitude': '34.03...
2016-07-07 12:54:00 1944073 600 2016-07-07T13:04:00 3022.0 34.046070 -118.233090 3014.0 34.056610 -118.237210 5721.0 30.0 One Way Monthly Pass {'longitude': '-118.23309', 'latitude': '34.04... {'longitude': '-118.23721', 'latitude': '34.05...
2016-07-07 12:59:00 1944067 600 2016-07-07T13:09:00 3076.0 34.040600 -118.253840 3005.0 34.048550 -118.259050 5957.0 365.0 One Way Flex Pass {'longitude': '-118.25384', 'latitude': '34.04... {'longitude': '-118.25905', 'latitude': '34.04...
2016-07-07 13:01:00 1944062 2880 2016-07-07T13:49:00 3031.0 34.044701 -118.252440 3031.0 34.044701 -118.252440 6137.0 365.0 Round Trip Flex Pass {'longitude': '-118.25244', 'latitude': '34.04... {'longitude': '-118.25244', 'latitude': '34.04...
2016-07-07 13:01:00 1944063 960 2016-07-07T13:17:00 3031.0 34.044701 -118.252440 3078.0 34.064281 -118.238940 6351.0 30.0 One Way Monthly Pass {'longitude': '-118.25244', 'latitude': '34.04... {'longitude': '-118.23894', 'latitude': '34.06...
2016-07-07 13:02:00 1944061 960 2016-07-07T13:18:00 3031.0 34.044701 -118.252440 3047.0 34.039982 -118.266400 6200.0 365.0 One Way Flex Pass {'longitude': '-118.25244', 'latitude': '34.04... {'longitude': '-118.2664', 'latitude': '34.039...
2016-07-07 13:03:00 1944059 720 2016-07-07T13:15:00 3063.0 34.049198 -118.252830 3005.0 34.048550 -118.259050 6110.0 30.0 One Way Monthly Pass {'longitude': '-118.25283', 'latitude': '34.04... {'longitude': '-118.25905', 'latitude': '34.04...
2016-07-07 13:03:00 1944058 360 2016-07-07T13:09:00 3042.0 34.049301 -118.238810 3030.0 34.051941 -118.243530 5856.0 30.0 One Way Monthly Pass {'longitude': '-118.23881', 'latitude': '34.04... {'longitude': '-118.24353', 'latitude': '34.05...
2016-07-07 13:04:00 1944054 120 2016-07-07T13:06:00 3018.0 34.043732 -118.260140 3018.0 34.043732 -118.260140 6217.0 30.0 Round Trip Monthly Pass {'longitude': '-118.26014', 'latitude': '34.04... {'longitude': '-118.26014', 'latitude': '34.04...
2016-07-07 13:04:00 1944057 660 2016-07-07T13:15:00 3054.0 34.039219 -118.236490 3030.0 34.051941 -118.243530 6717.0 30.0 One Way Monthly Pass {'longitude': '-118.23649', 'latitude': '34.03... {'longitude': '-118.24353', 'latitude': '34.05...
2016-07-07 13:04:00 1944055 480 2016-07-07T13:12:00 3031.0 34.044701 -118.252440 3076.0 34.040600 -118.253840 6332.0 365.0 One Way Flex Pass {'longitude': '-118.25244', 'latitude': '34.04... {'longitude': '-118.25384', 'latitude': '34.04...
2016-07-07 13:06:00 1944052 2100 2016-07-07T13:41:00 3006.0 34.045540 -118.256670 3033.0 34.040989 -118.255800 5965.0 30.0 One Way Monthly Pass {'longitude': '-118.25667', 'latitude': '34.04... {'longitude': '-118.2558', 'latitude': '34.040...
2016-07-07 13:07:00 1944050 600 2016-07-07T13:17:00 3018.0 34.043732 -118.260140 3007.0 34.050480 -118.254590 6608.0 30.0 One Way Monthly Pass {'longitude': '-118.26014', 'latitude': '34.04... {'longitude': '-118.25459', 'latitude': '34.05...
2016-07-07 13:07:00 1944048 420 2016-07-07T13:14:00 3014.0 34.056610 -118.237210 3016.0 34.052898 -118.241560 6557.0 30.0 One Way Monthly Pass {'longitude': '-118.23721', 'latitude': '34.05... {'longitude': '-118.24156', 'latitude': '34.05...
2016-07-07 13:07:00 1944049 960 2016-07-07T13:23:00 3037.0 34.034802 -118.231280 3063.0 34.049198 -118.252830 6123.0 30.0 One Way Monthly Pass {'longitude': '-118.23128', 'latitude': '34.03... {'longitude': '-118.25283', 'latitude': '34.04...
2016-07-07 13:07:00 1944051 1320 2016-07-07T13:29:00 3018.0 34.043732 -118.260140 3068.0 34.053200 -118.250950 6015.0 365.0 One Way Flex Pass {'longitude': '-118.26014', 'latitude': '34.04... {'longitude': '-118.25095', 'latitude': '34.05...
2016-07-07 13:08:00 1944046 1200 2016-07-07T13:28:00 3063.0 34.049198 -118.252830 3014.0 34.056610 -118.237210 6302.0 365.0 One Way Flex Pass {'longitude': '-118.25283', 'latitude': '34.04... {'longitude': '-118.23721', 'latitude': '34.05...
2016-07-07 13:08:00 1944047 240 2016-07-07T13:12:00 3034.0 34.042061 -118.263380 3019.0 34.038609 -118.260860 6029.0 365.0 One Way Flex Pass {'longitude': '-118.26338', 'latitude': '34.04... {'longitude': '-118.26086', 'latitude': '34.03...
2016-07-07 13:09:00 1944045 1140 2016-07-07T13:28:00 3063.0 34.049198 -118.252830 3014.0 34.056610 -118.237210 5835.0 30.0 One Way Monthly Pass {'longitude': '-118.25283', 'latitude': '34.04... {'longitude': '-118.23721', 'latitude': '34.05...
2016-07-07 13:09:00 1944043 1020 2016-07-07T13:26:00 3016.0 34.052898 -118.241560 3033.0 34.040989 -118.255800 6108.0 365.0 One Way Flex Pass {'longitude': '-118.24156', 'latitude': '34.05... {'longitude': '-118.2558', 'latitude': '34.040...
2016-07-07 13:10:00 1944042 360 2016-07-07T13:16:00 3005.0 34.048550 -118.259050 3052.0 34.051102 -118.264560 6295.0 365.0 One Way Flex Pass {'longitude': '-118.25905', 'latitude': '34.04... {'longitude': '-118.26456', 'latitude': '34.05...
2016-07-07 13:11:00 1981558 32700 2016-07-07T22:16:00 3005.0 34.048550 -118.259050 3021.0 34.045609 -118.237030 6139.0 30.0 One Way Monthly Pass {'longitude': '-118.25905', 'latitude': '34.04... {'longitude': '-118.23703', 'latitude': '34.04...
2016-07-07 13:11:00 1952019 6960 2016-07-07T15:07:00 3018.0 34.043732 -118.260140 3068.0 34.053200 -118.250950 6217.0 30.0 One Way Monthly Pass {'longitude': '-118.26014', 'latitude': '34.04... {'longitude': '-118.25095', 'latitude': '34.05...
2016-07-07 13:13:00 1944041 2160 2016-07-07T13:49:00 3047.0 34.039982 -118.266400 3030.0 34.051941 -118.243530 6528.0 365.0 One Way Flex Pass {'longitude': '-118.2664', 'latitude': '34.039... {'longitude': '-118.24353', 'latitude': '34.05...
2016-07-07 13:14:00 1944039 120 2016-07-07T13:16:00 3037.0 34.034802 -118.231280 3037.0 34.034802 -118.231280 6092.0 30.0 Round Trip Monthly Pass {'longitude': '-118.23128', 'latitude': '34.03... {'longitude': '-118.23128', 'latitude': '34.03...
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
2017-03-31 22:04:00 23656661 180 2017-03-31T22:07:00 3006.0 34.045540 -118.256668 3005.0 34.048550 -118.259048 6645.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.259048', 'latitude': '34.0...
2017-03-31 22:05:00 23656660 1320 2017-03-31T22:27:00 3055.0 34.044159 -118.251579 3058.0 34.035801 -118.233170 6717.0 365.0 One Way Flex Pass NaN {'longitude': '-118.23317', 'latitude': '34.03...
2017-03-31 22:05:00 23656659 300 2017-03-31T22:10:00 3008.0 34.046612 -118.262733 3052.0 34.051102 -118.264557 6569.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.264557', 'latitude': '34.0...
2017-03-31 22:06:00 23656658 1260 2017-03-31T22:27:00 3055.0 34.044159 -118.251579 3058.0 34.035801 -118.233170 6047.0 365.0 One Way Flex Pass NaN {'longitude': '-118.23317', 'latitude': '34.03...
2017-03-31 22:17:00 23656657 420 2017-03-31T22:24:00 3082.0 34.046520 -118.237411 3069.0 34.050880 -118.248253 6100.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.248253', 'latitude': '34.0...
2017-03-31 22:21:00 23656656 300 2017-03-31T22:26:00 3028.0 34.058319 -118.246094 3014.0 34.056610 -118.237213 6641.0 0.0 One Way Walk-up NaN {'longitude': '-118.237213', 'latitude': '34.0...
2017-03-31 22:23:00 23661008 3180 2017-03-31T23:16:00 3014.0 34.056610 -118.237213 3022.0 34.046070 -118.233093 6390.0 0.0 One Way Walk-up NaN {'longitude': '-118.233093', 'latitude': '34.0...
2017-03-31 22:26:00 23656655 480 2017-03-31T22:34:00 3064.0 34.046810 -118.256981 3034.0 34.042061 -118.263382 6520.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.263382', 'latitude': '34.0...
2017-03-31 22:26:00 23656654 180 2017-03-31T22:29:00 3057.0 34.035679 -118.270813 3025.0 34.032860 -118.268082 6053.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.268082', 'latitude': '34.0...
2017-03-31 22:27:00 23661005 2940 2017-03-31T23:16:00 3014.0 34.056610 -118.237213 3022.0 34.046070 -118.233093 6641.0 0.0 One Way Walk-up NaN {'longitude': '-118.233093', 'latitude': '34.0...
2017-03-31 22:30:00 23656653 840 2017-03-31T22:44:00 3025.0 34.032860 -118.268082 3057.0 34.035679 -118.270813 6238.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.270813', 'latitude': '34.0...
2017-03-31 22:47:00 23664842 5280 2017-04-01T00:15:00 3082.0 34.046520 -118.237411 3082.0 34.046520 -118.237411 6326.0 0.0 Round Trip Walk-up NaN {'longitude': '-118.237411', 'latitude': '34.0...
2017-03-31 22:48:00 23664841 5220 2017-04-01T00:15:00 3082.0 34.046520 -118.237411 3082.0 34.046520 -118.237411 6072.0 0.0 Round Trip Walk-up NaN {'longitude': '-118.237411', 'latitude': '34.0...
2017-03-31 22:48:00 23732455 70020 2017-04-01T18:15:00 3062.0 34.047749 -118.243172 3048.0 34.041691 -118.235352 5997.0 0.0 One Way Walk-up NaN {'longitude': '-118.235352', 'latitude': '34.0...
2017-03-31 23:02:00 23741000 76500 2017-04-01T20:17:00 3064.0 34.046810 -118.256981 3000.0 NaN NaN 6146.0 0.0 One Way Walk-up NaN NaN
2017-03-31 23:15:00 23661002 540 2017-03-31T23:24:00 3027.0 34.049980 -118.247162 3064.0 34.046810 -118.256981 5850.0 NaN One Way Monthly Pass NaN {'longitude': '-118.256981', 'latitude': '34.0...
2017-03-31 23:15:00 23661003 600 2017-03-31T23:25:00 3027.0 34.049980 -118.247162 3064.0 34.046810 -118.256981 6579.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.256981', 'latitude': '34.0...
2017-03-31 23:18:00 23661001 1020 2017-03-31T23:35:00 3019.0 34.038609 -118.260857 3066.0 34.063389 -118.236160 5767.0 0.0 One Way Walk-up NaN {'longitude': '-118.23616', 'latitude': '34.06...
2017-03-31 23:20:00 23661000 1320 2017-03-31T23:42:00 3069.0 34.050880 -118.248253 3006.0 34.045540 -118.256668 6100.0 0.0 One Way Walk-up NaN {'longitude': '-118.256668', 'latitude': '34.0...
2017-03-31 23:21:00 23660999 1260 2017-03-31T23:42:00 3069.0 34.050880 -118.248253 3006.0 34.045540 -118.256668 6247.0 0.0 One Way Walk-up NaN {'longitude': '-118.256668', 'latitude': '34.0...
2017-03-31 23:28:00 23660998 1020 2017-03-31T23:45:00 3031.0 34.044701 -118.252441 3055.0 34.044159 -118.251579 6311.0 0.0 One Way Walk-up NaN {'longitude': '-118.251579', 'latitude': '34.0...
2017-03-31 23:35:00 23660997 780 2017-03-31T23:48:00 3055.0 34.044159 -118.251579 3075.0 34.042110 -118.256187 6049.0 0.0 One Way Walk-up NaN {'longitude': '-118.256187', 'latitude': '34.0...
2017-03-31 23:36:00 23660996 720 2017-03-31T23:48:00 3055.0 34.044159 -118.251579 3075.0 34.042110 -118.256187 6441.0 0.0 One Way Walk-up NaN {'longitude': '-118.256187', 'latitude': '34.0...
2017-03-31 23:37:00 23660995 600 2017-03-31T23:47:00 3030.0 34.051941 -118.243530 3055.0 34.044159 -118.251579 6727.0 0.0 One Way Walk-up NaN {'longitude': '-118.251579', 'latitude': '34.0...
2017-03-31 23:41:00 23660994 720 2017-03-31T23:53:00 3055.0 34.044159 -118.251579 3035.0 34.048401 -118.260948 6143.0 30.0 One Way Monthly Pass NaN {'longitude': '-118.260948', 'latitude': '34.0...
2017-03-31 23:43:00 23660993 540 2017-03-31T23:52:00 3055.0 34.044159 -118.251579 3035.0 34.048401 -118.260948 5978.0 0.0 One Way Walk-up NaN {'longitude': '-118.260948', 'latitude': '34.0...
2017-03-31 23:44:00 23660992 480 2017-03-31T23:52:00 3055.0 34.044159 -118.251579 3035.0 34.048401 -118.260948 6478.0 0.0 One Way Walk-up NaN {'longitude': '-118.260948', 'latitude': '34.0...
2017-03-31 23:44:00 23660991 480 2017-03-31T23:52:00 3082.0 34.046520 -118.237411 3054.0 34.039219 -118.236488 6183.0 0.0 One Way Walk-up NaN {'longitude': '-118.236488', 'latitude': '34.0...
2017-03-31 23:45:00 23660990 420 2017-03-31T23:52:00 3082.0 34.046520 -118.237411 3054.0 34.039219 -118.236488 5900.0 0.0 One Way Walk-up NaN {'longitude': '-118.236488', 'latitude': '34.0...
2017-03-31 23:45:00 23664826 1260 2017-04-01T00:06:00 3078.0 34.064281 -118.238937 3029.0 34.048851 -118.246422 6207.0 0.0 One Way Walk-up NaN {'longitude': '-118.246422', 'latitude': '34.0...

132427 rows × 15 columns

In [286]:
plt.plot(df["Duration"].resample('M').mean())
plt.title("Average Trip Duration per Month")
plt.xlabel("Months")
plt.ylabel("Average Trip Duration (seconds)")
plt.show()

Above is a graph that depicts how average trip duration varies month to month. I decided to resample the data by month because of the short amount of seasons included in the time frame of the data set.

In [245]:
listMonths=pd.date_range('2016-07','2017-03', freq='MS').strftime("%Y-%m").tolist()
print listMonths
[u'2016-07', u'2016-08', u'2016-09', u'2016-10', u'2016-11', u'2016-12', u'2017-01', u'2017-02', u'2017-03']
In [246]:
realListMonths=[]
for row in listMonths:
    realListMonths.append(row.encode("utf-8"))
print realListMonths
['2016-07', '2016-08', '2016-09', '2016-10', '2016-11', '2016-12', '2017-01', '2017-02', '2017-03']
In [295]:
pd.value_counts(df["Passholder Type"][realListMonths[0]])
Out[295]:
Monthly Pass    9355
Flex Pass       1667
Walk-up          398
Name: Passholder Type, dtype: int64
In [304]:
for i in range(len(realListMonths)):
    plt.plot(pd.value_counts(df["Passholder Type"][realListMonths[i]]))
    plt.title(realListMonths[i])
    plt.xlabel("Passholder Type")
    plt.ylabel("Quantity")
    plt.show()

Above depicts the change in the occurence of each Passholder Type over the course of the months included in the dataset. I separated the data into separate monthly graphs because when I tried plotting the data in one graph, the output was a really confusing graph.

In [306]:
for i in range(len(realListMonths)):
    plt.plot(pd.value_counts(df["Trip Route Category"][realListMonths[i]]))
    plt.title(realListMonths[i])
    plt.xlabel("Trip Route Category")
    plt.ylabel("Quantity")
    plt.show()

Above is the same as the previous graph except for it's measuring trip route category frequencies.

In [310]:
for i in range(len(realListMonths)):
    plt.plot(pd.value_counts(df["Starting Station ID"][realListMonths[i]]), "o")
    plt.title(realListMonths[i])
    plt.xlabel("Starting Station ID")
    plt.ylabel("Quantity")
    plt.show()

This graph above shows the monthly change in quanitity of usage of each starting station.

In [312]:
for i in range(len(realListMonths)):
    plt.plot(pd.value_counts(df["Ending Station ID"][realListMonths[i]]), "o")
    plt.title(realListMonths[i])
    plt.xlabel("Ending Station ID")
    plt.ylabel("Quantity")
    plt.show()

This graph is the same as the previous one except that it's measuring ending station frequencies.

In [218]:
dict=(zip(tripRouteCategories, passholder_type_list))
print dict
[('Round Trip', 'Monthly Pass'), ('Round Trip', 'Monthly Pass'), ('Round Trip', 'Flex Pass'), ('Round Trip', 'Flex Pass'), ('Round Trip', 'Walk-up'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('Round Trip', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('Round Trip', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('Round Trip', 'Monthly Pass'), ('One Way', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('Round Trip', 'Monthly Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Monthly Pass'), 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In [288]:
a=np.unique(dict, axis=0)
b=[]
for i in a:
    b.append(tuple(i))
print b
[('One Way', 'Flex Pass'), ('One Way', 'Monthly Pass'), ('One Way', 'Staff Annual'), ('One Way', 'Walk-up'), ('Round Trip', 'Flex Pass'), ('Round Trip', 'Monthly Pass'), ('Round Trip', 'Staff Annual'), ('Round Trip', 'Walk-up')]
In [289]:
for row in b:
    print row, dict.count(row)
('One Way', 'Flex Pass') 9034
('One Way', 'Monthly Pass') 77532
('One Way', 'Staff Annual') 299
('One Way', 'Walk-up') 32777
('Round Trip', 'Flex Pass') 483
('Round Trip', 'Monthly Pass') 3772
('Round Trip', 'Staff Annual') 83
('Round Trip', 'Walk-up') 8447

Above is the breakdown of Trip Route Category-Passholder Type combinations. I think it would make sense for the one way, monthly pass combination to be most frequent given that lots of people are trying to get to work and don't worry about taking the exact bike they started with back home. Also, Staff Annual combinations are at the bottom because ordinary users probably outnumber staff.

In [228]:
ending_station_ids=[]
for row in df["Ending Station ID"]:
    ending_station_ids.append(row)
print ending_station_ids
[3014.0, 3014.0, 3016.0, 3016.0, 3032.0, 3054.0, 3014.0, 3005.0, 3031.0, 3078.0, 3047.0, 3005.0, 3030.0, 3018.0, 3030.0, 3076.0, 3033.0, 3007.0, 3016.0, 3063.0, 3068.0, 3014.0, 3019.0, 3014.0, 3033.0, 3052.0, 3021.0, 3068.0, 3030.0, 3037.0, 3006.0, 3006.0, 3014.0, 3016.0, 3042.0, 3032.0, 3014.0, 3036.0, 3030.0, 3030.0, 3053.0, 3065.0, 3035.0, 3014.0, 3016.0, 3028.0, 3014.0, 3022.0, 3018.0, 3055.0, 3033.0, 3058.0, 3058.0, 3065.0, 3051.0, 3014.0, 3019.0, 3065.0, 3065.0, 3052.0, 3052.0, 3006.0, 3014.0, 3030.0, 3016.0, 3038.0, 3038.0, 3047.0, 3031.0, 3014.0, 3065.0, 3019.0, 3019.0, 3018.0, 3018.0, 3047.0, 3042.0, 3014.0, 3063.0, 3075.0, 3055.0, 3007.0, 3063.0, 3065.0, 3014.0, 3032.0, 3063.0, 3065.0, 3067.0, 3016.0, 3018.0, 3047.0, 3042.0, 3016.0, 3005.0, 3040.0, 3005.0, 3014.0, 3005.0, 3030.0, 3049.0, 3031.0, 3042.0, 3042.0, 3016.0, 3006.0, 3005.0, 3075.0, 3065.0, 3066.0, 3016.0, 3006.0, 3016.0, 3006.0, 3062.0, 3020.0, 3062.0, 3067.0, 3006.0, 3078.0, 3051.0, 3049.0, 3042.0, 3038.0, 3030.0, 3078.0, 3020.0, 3031.0, 3042.0, 3021.0, 3033.0, 3052.0, 3052.0, 3014.0, 3014.0, 3030.0, 3006.0, 3006.0, 3018.0, 3030.0, 3049.0, 3021.0, 3022.0, 3021.0, 3035.0, 3035.0, 3058.0, 3035.0, 3018.0, 3066.0, 3054.0, 3018.0, 3018.0, 3034.0, 3034.0, 3022.0, 3021.0, 3021.0, 3021.0, 3052.0, 3006.0, 3035.0, 3034.0, 3062.0, 3034.0, 3006.0, 3021.0, 3021.0, 3042.0, 3005.0, 3006.0, 3031.0, 3037.0, 3066.0, 3037.0, 3037.0, 3080.0, 3005.0, 3051.0, 3031.0, 3031.0, 3049.0, 3045.0, 3067.0, 3067.0, 3047.0, 3047.0, 3042.0, 3042.0, 3049.0, 3005.0, 3038.0, 3031.0, 3062.0, 3062.0, 3040.0, 3038.0, 3034.0, 3014.0, 3030.0, 3021.0, 3075.0, 3056.0, 3052.0, 3063.0, 3035.0, 3016.0, 3079.0, 3035.0, 3030.0, 3005.0, 3032.0, 3008.0, 3030.0, 3030.0, 3063.0, 3058.0, 3030.0, 3068.0, 3021.0, 3030.0, 3005.0, 3042.0, 3045.0, 3045.0, 3007.0, 3075.0, 3022.0, 3036.0, 3080.0, 3007.0, 3055.0, 3030.0, 3030.0, 3076.0, 4108.0, 3019.0, 3016.0, 3079.0, 3035.0, 3060.0, 3042.0, 3005.0, 3006.0, 3045.0, 3030.0, 3069.0, 3014.0, 3051.0, 3008.0, 3034.0, 3030.0, 3005.0, 3035.0, 3005.0, 3069.0, 3065.0, 3049.0, 3030.0, 3067.0, 3065.0, 3014.0, 3021.0, 3021.0, 3028.0, 3036.0, 3022.0, 3022.0, 3019.0, 3038.0, 3014.0, 3052.0, 3030.0, 3038.0, 3014.0, 3014.0, 3058.0, 3069.0, 3030.0, 3066.0, 3051.0, 3062.0, 3029.0, 3063.0, 3030.0, 3030.0, 3030.0, 3063.0, 3021.0, 3016.0, 3068.0, 3014.0, 3014.0, 3014.0, 3036.0, 3014.0, 3035.0, 3035.0, 3008.0, 3076.0, 3076.0, 3055.0, 3042.0, 3068.0, 3065.0, 3014.0, 3063.0, 3016.0, 3062.0, 3007.0, 3007.0, 3007.0, 3068.0, 3022.0, 3006.0, 3066.0, 3023.0, 3038.0, 3069.0, 3052.0, 3005.0, 3036.0, 3049.0, 3062.0, 3029.0, 3019.0, 3035.0, 3021.0, 3018.0, 3020.0, 3038.0, 3069.0, 3028.0, 3028.0, 3034.0, 3034.0, 3031.0, 3042.0, 3035.0, 3042.0, 3074.0, 3066.0, 3006.0, 3006.0, 3065.0, 3075.0, 3075.0, 3008.0, 3038.0, 3035.0, 3052.0, 3005.0, 3067.0, 3042.0, 3016.0, 3052.0, 3007.0, 3060.0, 3055.0, 3055.0, 3032.0, 3038.0, 3063.0, 3067.0, 3028.0, 3058.0, 3058.0, 3026.0, 3075.0, 3075.0, 3035.0, 3038.0, 3049.0, 3008.0, 3055.0, 3005.0, 3063.0, 3006.0, 3067.0, 3021.0, 3021.0, 3042.0, 3032.0, 3065.0, 3058.0, 3065.0, 3074.0, 3075.0, 3069.0, 3031.0, 3051.0, 3031.0, 3031.0, 3074.0, 3005.0, 3006.0, 3007.0, 3042.0, 3038.0, 3036.0, 3005.0, 3026.0, 3049.0, 3018.0, 3074.0, 3068.0, 3063.0, 3049.0, 3051.0, 3038.0, 3057.0, 3036.0, 3062.0, 3074.0, 3074.0, 3055.0, 3067.0, 3022.0, 3042.0, 3042.0, 3075.0, 3005.0, 3016.0, 3005.0, 3005.0, 3016.0, 3005.0, 3042.0, 3074.0, 3031.0, 3006.0, 3026.0, 3063.0, 3054.0, 3063.0, 3028.0, 3042.0, 3053.0, 3022.0, 3027.0, 3027.0, 3014.0, 3031.0, 3005.0, 3014.0, 3047.0, 3038.0, 3051.0, 3069.0, 3014.0, 3035.0, 3035.0, 3053.0, 3076.0, 3037.0, 3037.0, 3006.0, 3026.0, 3028.0, 3042.0, 3025.0, 3005.0, 3005.0, 3031.0, 3031.0, 3038.0, 3022.0, 3022.0, 3014.0, 3005.0, 3052.0, 3021.0, 3030.0, 3030.0, 3062.0, 3006.0, 3036.0, 3008.0, 3058.0, 3058.0, 3008.0, 3008.0, 3021.0, 3005.0, 3036.0, 3036.0, 3031.0, 3067.0, 3067.0, 3063.0, 3038.0, 3075.0, 3075.0, 3067.0, 3068.0, 3018.0, 3035.0, 3035.0, 3035.0, 3040.0, 3052.0, 3075.0, 3016.0, 3016.0, 3047.0, 3014.0, 3047.0, 3069.0, 3029.0, 3008.0, 3008.0, 3042.0, 3042.0, 3006.0, 3047.0, 3006.0, 3006.0, 3021.0, 3034.0, 3034.0, 3023.0, 3023.0, 3034.0, 3034.0, 3014.0, 3014.0, 3031.0, 3031.0, 3075.0, 3052.0, 3045.0, 3006.0, 3006.0, 3062.0, 3062.0, 3075.0, 3021.0, 3018.0, 3018.0, 3016.0, 3075.0, 3075.0, 3063.0, 3063.0, 3005.0, 3065.0, 3065.0, 3056.0, 3038.0, 3006.0, 3056.0, 3066.0, 3006.0, 3014.0, 3014.0, 3058.0, 3063.0, 3006.0, 3062.0, 3053.0, 3032.0, 3049.0, 3049.0, 3036.0, 3036.0, 3022.0, 3074.0, 3075.0, 3049.0, 3049.0, 3021.0, 3034.0, 3034.0, 3006.0, 3005.0, 3067.0, 3076.0, 3063.0, 3075.0, 3021.0, 3021.0, 3074.0, 3074.0, 3038.0, 3066.0, 3069.0, 3006.0, 3031.0, 3031.0, 3031.0, 3031.0, 3031.0, 3031.0, 3022.0, 3014.0, 3067.0, 3035.0, 3035.0, 3067.0, 3036.0, 3037.0, 3042.0, 3028.0, 3005.0, 3042.0, 3035.0, 3035.0, 3014.0, 3036.0, 3075.0, 3075.0, 3036.0, 3038.0, 3032.0, 3036.0, 3051.0, 3031.0, 3035.0, 3069.0, 3033.0, 3042.0, 3021.0, 3031.0, 3063.0, 3065.0, 3030.0, 3030.0, 3062.0, 3068.0, 3030.0, 3075.0, 3023.0, 3069.0, 3062.0, 3019.0, 3069.0, 3074.0, 3060.0, 3060.0, 3021.0, 3028.0, 3077.0, 3033.0, 3063.0, 3034.0, 3034.0, 3063.0, 3038.0, 3069.0, 3069.0, 3007.0, 3057.0, 3076.0, 3066.0, 3034.0, 3030.0, 3032.0, 3031.0, 3067.0, 3079.0, 3032.0, 3021.0, 3032.0, 3021.0, 3006.0, 3021.0, 3049.0, 3069.0, 3069.0, 3069.0, 3014.0, 3035.0, 3066.0, 3054.0, 3054.0, 3021.0, 3058.0, 3005.0, 3023.0, 3005.0, 3032.0, 3049.0, 3051.0, 3051.0, 3066.0, 3075.0, 3037.0, 3075.0, 3037.0, 3037.0, 3021.0, 3014.0, 3008.0, 3021.0, 3030.0, 3060.0, 3008.0, 3008.0, 3005.0, 3074.0, 3074.0, 3035.0, 3054.0, 3051.0, 3035.0, 3035.0, 3020.0, 3068.0, 3030.0, 3030.0, 3068.0, 3022.0, 3055.0, 3055.0, 3040.0, 3052.0, 3055.0, 3069.0, 3014.0, 3014.0, 3047.0, 3021.0, 3021.0, 3030.0, 3034.0, 3067.0, 3067.0, 3030.0, 3034.0, 3059.0, 3022.0, 3031.0, 3031.0, 3005.0, 3029.0, 3029.0, 3067.0, 3022.0, 3035.0, 3035.0, 3067.0, 3026.0, 3026.0, 3076.0, 3006.0, 3053.0, 3076.0, 3075.0, 3028.0, 3075.0, 3032.0, 3074.0, 3018.0, 3018.0, 3040.0, 3078.0, 3078.0, 3042.0, 3052.0, 3042.0, 3027.0, 3062.0, 3021.0, 3027.0, 3030.0, 3006.0, 3006.0, 3036.0, 3036.0, 3014.0, 3031.0, 3021.0, 3021.0, 3034.0, 3034.0, 3038.0, 3031.0, 3031.0, 3057.0, 3031.0, 3038.0, 3038.0, 3053.0, 3069.0, 3069.0, 3053.0, 3069.0, 3042.0, 3069.0, 3058.0, 3006.0, 3032.0, 3052.0, 3018.0, 3022.0, 3030.0, 3042.0, 3023.0, 3057.0, 3033.0, 3021.0, 3069.0, 3069.0, 3023.0, 3023.0, 3047.0, 3075.0, 3031.0, 3031.0, 3055.0, 3078.0, 3021.0, 3021.0, 3049.0, 3006.0, 3006.0, 3063.0, 3056.0, 3021.0, 3021.0, 3030.0, 3063.0, 3030.0, 3042.0, 3042.0, 3030.0, 3036.0, 3042.0, 3042.0, 3036.0, 3035.0, 3035.0, 3053.0, 3022.0, 3069.0, 3014.0, 3079.0, 3014.0, 3021.0, 3018.0, 3028.0, 3049.0, 3049.0, 3022.0, 3031.0, 3058.0, 3058.0, 3059.0, 3052.0, 3052.0, 3065.0, 3065.0, 3063.0, 3078.0, 3078.0, 3049.0, 3062.0, 3062.0, 3049.0, 3005.0, 3062.0, 3022.0, 3022.0, 3035.0, 3035.0, 3062.0, 3067.0, 3067.0, 3067.0, 3038.0, 3045.0, 3078.0, 3042.0, 3038.0, 3038.0, 3008.0, 3008.0, 3075.0, 3062.0, 3078.0, 3027.0, 3040.0, 3040.0, 3075.0, 3075.0, 3074.0, 3074.0, 3052.0, 3037.0, 3052.0, 3030.0, 3005.0, 3022.0, 3031.0, 3051.0, 3051.0, 3023.0, 3023.0, 3014.0, 3027.0, 3027.0, 3063.0, 3036.0, 3036.0, 3035.0, 3035.0, 3005.0, 3052.0, 3018.0, 3005.0, 3062.0, 3062.0, 3063.0, 3063.0, 3063.0, 3053.0, 3031.0, 3031.0, 3065.0, 3065.0, 3065.0, 3034.0, 3034.0, 3034.0, 3042.0, 3042.0, 3055.0, 3053.0, 3062.0, 3005.0, 3005.0, 3021.0, 3031.0, 3037.0, 3037.0, 3037.0, 3031.0, 3005.0, 3031.0, 3049.0, 3040.0, 3062.0, 3062.0, 3005.0, 3005.0, 3031.0, 3034.0, 3026.0, 3026.0, 3047.0, 3031.0, 3031.0, 3005.0, 3049.0, 3022.0, 3022.0, 3069.0, 3031.0, 3031.0, 3005.0, 3028.0, 3042.0, 3067.0, 3042.0, 3058.0, 3006.0, 3014.0, 3005.0, 3014.0, 3063.0, 3006.0, 3030.0, 3005.0, 3040.0, 3052.0, 3021.0, 3058.0, 3058.0, 3069.0, 3028.0, 3058.0, 3056.0, 3006.0, 3035.0, 3054.0, 3069.0, 3018.0, 3067.0, 3075.0, 3008.0, 3008.0, 3007.0, 3007.0, 3022.0, 3077.0, 3021.0, 3021.0, 3038.0, 3068.0, 3045.0, 3068.0, 3053.0, 3020.0, 3031.0, 3022.0, 3022.0, 3007.0, 3022.0, 3008.0, 3031.0, 3031.0, 3058.0, 3052.0, 3006.0, 3055.0, 3034.0, 3049.0, 3069.0, 3040.0, 3075.0, 3029.0, 3028.0, 3028.0, 3042.0, 3042.0, 3075.0, 3006.0, 3030.0, 3058.0, 3036.0, 3049.0, 3060.0, 3036.0, 3036.0, 3067.0, 3067.0, 3055.0, 3069.0, 3034.0, 3022.0, 3042.0, 3042.0, 3021.0, 3021.0, 3014.0, 3014.0, 3007.0, 3047.0, 3038.0, 3021.0, 3021.0, 3022.0, 3035.0, 3038.0, 3067.0, 3036.0, 3030.0, 3005.0, 3052.0, 3005.0, 3037.0, 3037.0, 3034.0, 3034.0, 3007.0, 3007.0, 3068.0, 3038.0, 3006.0, 3049.0, 3049.0, 3077.0, 3058.0, 3058.0, 3067.0, 3058.0, 3058.0, 3067.0, 3036.0, 3067.0, 3005.0, 3014.0, 3069.0, 3055.0, 3063.0, 3063.0, 3034.0, 3062.0, 3062.0, 3040.0, 3031.0, 3059.0, 3075.0, 3075.0, 3005.0, 3021.0, 3030.0, 3030.0, 3006.0, 3032.0, 3022.0, 3066.0, 3066.0, 3031.0, 3058.0, 3018.0, 3022.0, 3005.0, 3005.0, 3075.0, 3075.0, 3049.0, 3080.0, 3080.0, 3014.0, 3078.0, 3034.0, 3030.0, 3040.0, 3010.0, 3010.0, 3035.0, 3038.0, 3021.0, 3031.0, 3042.0, 3006.0, 3063.0, 3063.0, 3021.0, 3021.0, 3018.0, 3058.0, 3035.0, 3035.0, 3069.0, 3069.0, 3028.0, 3062.0, 3075.0, 3032.0, 3032.0, 3052.0, 3052.0, 3032.0, 3035.0, 3038.0, 3038.0, 3054.0, 3054.0, 3068.0, 3063.0, 3036.0, 3036.0, 3031.0, 3067.0, 3067.0, 3034.0, 3032.0, 3032.0, 3034.0, 3014.0, 3034.0, 3026.0, 3042.0, 3042.0, 3075.0, 3042.0, 3032.0, 3032.0, 3034.0, 3038.0, 3068.0, 3047.0, 3032.0, 3032.0, 3058.0, 3006.0, 3028.0, 3028.0, 3055.0, 3074.0, 3074.0, 3029.0, 3029.0, 3049.0, 3067.0, 3005.0, 3038.0, 3006.0, 3049.0, 3037.0, 3005.0, 3005.0, 3067.0, 3067.0, 3063.0, 3022.0, 3063.0, 3031.0, 3022.0, 3031.0, 3005.0, 3031.0, 3005.0, 3005.0, 3051.0, 3036.0, 3005.0, 3005.0, 3019.0, 3037.0, 3037.0, 3005.0, 3005.0, 3054.0, 3034.0, 3005.0, 3034.0, 3051.0, 3006.0, 3075.0, 3075.0, 3075.0, 3075.0, 3006.0, 3006.0, 3035.0, 3035.0, 3069.0, 3069.0, 3023.0, 3023.0, 3067.0, 3067.0, 3005.0, 3033.0, 3033.0, 3008.0, 3029.0, 3029.0, 3035.0, 3035.0, 3021.0, 3031.0, 3049.0, 3049.0, 3026.0, 3026.0, 3049.0, 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3008.0, 3062.0, 3067.0, 3042.0, 3056.0, 3051.0, 3075.0, 3011.0, 3054.0, 3008.0, 3019.0, 3014.0, 3082.0, 3023.0, 3022.0, 3005.0, 3005.0, 3006.0, 3011.0, 3011.0, 3022.0, 3022.0, 3029.0, 3022.0, 3062.0, 3076.0, 3042.0, 3076.0, 3038.0, 3076.0, 3027.0, 3031.0, 3048.0, 3018.0, 3075.0, 3042.0, 3018.0, 3038.0, 3082.0, 3082.0, 3035.0, 3042.0, 3082.0, 3067.0, 3048.0, 3034.0, 3049.0, 3005.0, 3005.0, 3022.0, 3022.0, 3065.0, 3014.0, 3042.0, 3014.0, 3025.0, 3056.0, 3047.0, 3075.0, 3074.0, 3064.0, 3005.0, 3027.0, 3054.0, 3034.0, 3065.0, 3065.0, 3014.0, 3014.0, 3052.0, 3047.0, 3014.0, 3014.0, 3008.0, 3082.0, 3078.0, 3082.0, 3037.0, 3078.0, 3042.0, 3069.0, 3042.0, 3005.0, 3063.0, 3042.0, 3005.0, 3023.0, 3014.0, 3023.0, 3023.0, 3042.0, 3022.0, 3005.0, 3042.0, 3005.0, 3006.0, 3081.0, 3042.0, 3042.0, 3082.0, 3055.0, 3032.0, 3054.0, 3042.0, 3014.0, 3064.0, 3082.0, 3029.0, 3031.0, 3051.0, 3014.0, 3074.0, 3010.0, 3048.0, 3042.0, 3063.0, 3014.0, 3069.0, 3038.0, 3074.0, 3032.0, 3031.0, 3064.0, 3005.0, 3082.0, 3065.0, 3023.0, 3023.0, 3082.0, 3082.0, 3010.0, 3058.0, 3042.0, 3006.0, 3035.0, 3014.0, 3014.0, 3007.0, 3076.0, 3076.0, 3067.0, 3005.0, 3062.0, 3082.0, 3018.0, 3018.0, 3030.0, 3029.0, 3055.0, 3056.0, 3069.0, 3042.0, 3014.0, 3023.0, 3082.0, 3082.0, 3014.0, 3000.0, 3062.0, 3023.0, 3022.0, 3022.0, 3062.0, 3022.0, 3055.0, 3042.0, 3022.0, 3040.0, 3042.0, 3023.0, 3078.0, 3014.0, 3014.0, 3069.0, 3078.0, 3014.0, 3078.0, 3031.0, 3052.0, 3065.0, 3011.0, 3005.0, 3014.0, 3014.0, 3035.0, 3030.0, 3035.0, 3064.0, 3074.0, 3062.0, 3023.0, 3008.0, 3062.0, 3066.0, 3027.0, 3078.0, 3049.0, 3049.0, 3034.0, 3052.0, 3064.0, 3064.0, 3063.0, 3042.0, 3069.0, 3042.0, 3042.0, 3048.0, 3064.0, 3052.0, 3007.0, 3082.0, 3078.0, 3057.0, 3082.0, 3031.0, 3067.0, 3048.0, 3082.0, 3052.0, 3034.0, 3067.0, 3067.0, 3067.0, 3038.0, 3018.0, 3008.0, 3067.0, 3008.0, 3008.0, 3067.0, 3008.0, 3067.0, 3008.0, 3067.0, 3062.0, 3075.0, 3055.0, 3047.0, 3034.0, 3082.0, 3023.0, 3037.0, 3063.0, 3023.0, 3029.0, 3082.0, 3000.0, 3022.0, 3068.0, 3052.0, 3029.0, 3029.0, 3067.0, 3042.0, 3005.0, 3037.0, 3046.0, 3046.0, 3048.0, 3011.0, 3011.0, 3011.0, 3011.0, 3011.0, 3005.0, 3058.0, 3052.0, 3058.0, 3069.0, 3014.0, 3022.0, 3034.0, 3025.0, 3022.0, 3057.0, 3082.0, 3082.0, 3048.0, 3000.0, 3064.0, 3064.0, 3066.0, 3006.0, 3006.0, 3055.0, 3075.0, 3075.0, 3055.0, 3035.0, 3035.0, 3035.0, 3054.0, 3054.0, 3029.0]
In [222]:
bikeids=[]
for row in df["Bike ID"]:
    bikeids.append(row)
print bikeids
[6281.0, 6281.0, 5861.0, 5861.0, 6674.0, 6717.0, 5721.0, 5957.0, 6137.0, 6351.0, 6200.0, 6110.0, 5856.0, 6217.0, 6717.0, 6332.0, 5965.0, 6608.0, 6557.0, 6123.0, 6015.0, 6302.0, 6029.0, 5835.0, 6108.0, 6295.0, 6139.0, 6217.0, 6528.0, 6092.0, 6102.0, 6011.0, 6185.0, 6590.0, 6092.0, 5861.0, 6370.0, 5965.0, 6579.0, 6108.0, 6691.0, 5801.0, 5735.0, 5860.0, 6114.0, 6469.0, 6487.0, 6140.0, 6528.0, 6011.0, 6348.0, 6389.0, 6254.0, 5783.0, 5922.0, 6432.0, 6029.0, 6040.0, 6558.0, 5916.0, 6433.0, 6348.0, 5897.0, 6370.0, 6369.0, 6011.0, 6305.0, 6404.0, 6558.0, 6015.0, 6185.0, 5928.0, 6528.0, 5759.0, 6524.0, 6608.0, 5856.0, 5951.0, 6404.0, 6588.0, 6357.0, 6295.0, 6528.0, 5801.0, 5909.0, 6690.0, 6029.0, 5996.0, 6370.0, 6125.0, 6214.0, 6103.0, 6108.0, 6038.0, 6123.0, 5912.0, 6674.0, 6217.0, 5927.0, 6060.0, 5916.0, 5725.0, 5890.0, 5912.0, 6038.0, 6690.0, 5816.0, 6031.0, 6621.0, 6151.0, 5936.0, 6053.0, 6419.0, 5986.0, 6674.0, 6228.0, 5928.0, 6595.0, 6313.0, 6528.0, 6275.0, 5751.0, 5927.0, 6500.0, 5856.0, 6259.0, 5805.0, 5936.0, 6213.0, 6059.0, 5916.0, 6059.0, 6262.0, 5863.0, 6634.0, 5861.0, 6192.0, 5751.0, 5735.0, 5829.0, 6123.0, 5972.0, 6093.0, 6437.0, 6433.0, 6262.0, 6140.0, 6059.0, 6009.0, 5985.0, 6476.0, 5910.0, 6267.0, 6354.0, 6579.0, 6272.0, 6584.0, 6674.0, 6556.0, 6059.0, 6579.0, 6123.0, 5755.0, 6089.0, 5964.0, 6433.0, 6354.0, 5755.0, 6604.0, 5856.0, 5721.0, 6403.0, 6092.0, 6397.0, 6213.0, 6140.0, 6210.0, 6137.0, 6137.0, 6204.0, 6437.0, 6440.0, 6210.0, 5972.0, 6354.0, 6139.0, 6353.0, 6092.0, 6213.0, 5916.0, 5897.0, 5982.0, 6262.0, 6492.0, 6670.0, 6110.0, 5922.0, 6031.0, 6481.0, 5916.0, 5755.0, 6141.0, 6031.0, 6440.0, 6267.0, 6141.0, 5856.0, 5886.0, 5890.0, 6481.0, 6676.0, 6371.0, 5936.0, 6357.0, 6157.0, 6397.0, 6614.0, 5922.0, 6015.0, 5829.0, 6326.0, 6288.0, 6308.0, 5833.0, 6056.0, 6108.0, 5980.0, 6389.0, 5886.0, 5833.0, 6608.0, 6056.0, 6066.0, 6481.0, 6305.0, 6065.0, 6603.0, 5799.0, 6428.0, 6059.0, 6283.0, 5927.0, 6217.0, 5936.0, 6623.0, 6360.0, 5890.0, 6254.0, 5985.0, 5924.0, 6031.0, 5977.0, 6481.0, 6357.0, 6066.0, 6360.0, 5955.0, 6371.0, 6634.0, 5721.0, 5951.0, 5798.0, 5977.0, 6326.0, 6015.0, 6295.0, 6231.0, 5909.0, 6603.0, 6366.0, 5951.0, 6368.0, 6568.0, 6634.0, 6053.0, 6348.0, 6093.0, 6076.0, 6561.0, 5936.0, 5861.0, 6531.0, 6011.0, 6056.0, 6674.0, 6326.0, 6576.0, 6021.0, 5861.0, 5925.0, 6561.0, 6057.0, 6174.0, 6272.0, 5886.0, 6298.0, 6676.0, 5897.0, 5924.0, 6658.0, 6056.0, 6203.0, 5862.0, 5970.0, 6015.0, 5862.0, 5861.0, 5821.0, 6026.0, 5886.0, 6677.0, 6565.0, 6213.0, 6203.0, 5899.0, 5861.0, 6151.0, 5916.0, 6447.0, 6110.0, 6621.0, 6295.0, 5996.0, 6203.0, 6412.0, 5969.0, 5879.0, 6450.0, 6531.0, 6603.0, 6634.0, 5721.0, 6272.0, 6254.0, 6360.0, 6031.0, 6059.0, 6308.0, 6298.0, 6026.0, 5862.0, 5945.0, 6158.0, 6587.0, 5974.0, 6677.0, 6565.0, 6396.0, 6203.0, 6315.0, 6110.0, 5948.0, 6293.0, 6527.0, 5798.0, 5924.0, 6192.0, 6283.0, 5847.0, 6461.0, 6469.0, 5784.0, 6291.0, 6603.0, 6298.0, 6581.0, 6313.0, 6080.0, 5879.0, 6357.0, 6534.0, 6295.0, 6217.0, 5810.0, 5897.0, 6654.0, 6141.0, 6201.0, 5784.0, 6534.0, 5873.0, 6081.0, 6494.0, 5974.0, 5754.0, 6039.0, 5849.0, 5871.0, 6576.0, 6481.0, 6036.0, 6621.0, 5948.0, 6509.0, 6429.0, 5899.0, 6440.0, 6311.0, 6031.0, 6390.0, 6653.0, 6123.0, 6254.0, 6292.0, 5802.0, 5821.0, 6671.0, 5849.0, 5737.0, 6108.0, 6072.0, 6319.0, 5957.0, 6252.0, 6606.0, 5829.0, 5972.0, 6390.0, 6026.0, 6092.0, 6437.0, 6326.0, 5727.0, 6520.0, 5806.0, 5767.0, 6297.0, 6429.0, 5814.0, 6376.0, 6357.0, 6440.0, 6057.0, 6389.0, 6212.0, 6463.0, 5893.0, 6036.0, 6217.0, 6174.0, 6281.0, 5767.0, 6357.0, 6234.0, 5727.0, 6066.0, 5861.0, 6521.0, 5974.0, 6157.0, 6281.0, 6174.0, 6018.0, 6073.0, 6653.0, 5806.0, 5974.0, 6641.0, 5929.0, 5751.0, 5935.0, 6204.0, 6357.0, 6437.0, 6677.0, 5972.0, 5911.0, 5953.0, 5727.0, 6297.0, 6110.0, 5893.0, 6158.0, 5924.0, 6463.0, 5974.0, 5977.0, 5846.0, 6322.0, 5754.0, 5922.0, 6674.0, 6319.0, 5725.0, 6185.0, 6040.0, 6463.0, 6618.0, 6502.0, 6123.0, 6297.0, 6481.0, 6463.0, 6203.0, 6353.0, 6174.0, 6110.0, 6370.0, 6502.0, 6357.0, 6110.0, 6481.0, 6015.0, 6025.0, 6502.0, 6108.0, 6370.0, 6576.0, 6366.0, 6103.0, 6066.0, 6082.0, 6152.0, 5974.0, 6353.0, 5898.0, 6078.0, 6293.0, 6520.0, 6204.0, 6045.0, 6492.0, 6322.0, 6581.0, 6348.0, 5727.0, 6151.0, 6492.0, 5802.0, 5986.0, 6200.0, 6048.0, 6021.0, 5974.0, 6579.0, 5802.0, 6480.0, 6457.0, 6055.0, 5893.0, 6230.0, 6367.0, 6531.0, 5735.0, 6653.0, 6671.0, 6123.0, 6577.0, 6203.0, 6194.0, 6323.0, 6144.0, 5898.0, 5916.0, 6319.0, 6682.0, 6728.0, 6018.0, 6045.0, 6072.0, 5898.0, 5908.0, 5802.0, 5849.0, 5741.0, 5907.0, 5898.0, 5806.0, 5748.0, 6140.0, 5907.0, 6204.0, 6322.0, 5898.0, 6288.0, 6084.0, 6581.0, 6293.0, 6450.0, 5752.0, 6320.0, 6690.0, 6133.0, 6502.0, 5897.0, 6706.0, 6059.0, 6634.0, 6706.0, 6634.0, 6481.0, 6450.0, 6059.0, 5844.0, 6076.0, 5814.0, 6450.0, 6481.0, 6690.0, 5832.0, 6220.0, 6366.0, 6217.0, 6084.0, 5828.0, 5871.0, 5806.0, 5828.0, 6158.0, 6481.0, 6315.0, 5924.0, 5784.0, 6533.0, 6717.0, 6480.0, 6351.0, 6155.0, 6140.0, 6482.0, 6390.0, 6220.0, 6059.0, 5846.0, 6144.0, 6320.0, 6387.0, 6492.0, 6359.0, 5977.0, 5810.0, 6351.0, 6011.0, 5752.0, 6576.0, 6475.0, 5784.0, 6036.0, 6495.0, 5821.0, 6491.0, 6061.0, 6592.0, 6194.0, 6495.0, 6036.0, 6520.0, 6252.0, 6481.0, 6315.0, 6223.0, 6706.0, 5814.0, 6619.0, 5790.0, 6223.0, 6404.0, 6107.0, 5814.0, 6220.0, 6634.0, 6315.0, 6262.0, 6481.0, 6110.0, 5814.0, 6525.0, 6541.0, 6447.0, 6010.0, 5847.0, 6371.0, 6585.0, 5814.0, 6193.0, 6651.0, 6463.0, 6461.0, 5899.0, 5890.0, 5988.0, 5806.0, 6334.0, 5731.0, 6144.0, 5716.0, 5821.0, 6447.0, 6481.0, 6651.0, 6492.0, 5847.0, 6107.0, 6587.0, 6015.0, 6139.0, 6059.0, 6621.0, 6551.0, 5879.0, 6367.0, 6020.0, 6272.0, 5890.0, 5979.0, 5725.0, 6374.0, 6121.0, 6527.0, 6429.0, 6236.0, 6016.0, 6653.0, 5847.0, 6015.0, 6193.0, 6728.0, 6541.0, 5970.0, 6561.0, 6224.0, 6180.0, 5910.0, 6006.0, 5948.0, 6286.0, 6404.0, 6026.0, 6376.0, 6100.0, 6185.0, 6054.0, 5986.0, 5993.0, 6651.0, 6406.0, 6020.0, 5821.0, 6036.0, 6495.0, 6018.0, 6155.0, 5871.0, 6510.0, 6510.0, 6133.0, 5996.0, 6367.0, 6114.0, 5784.0, 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5898.0, 5767.0, 5848.0, 6577.0, 6076.0, 5842.0, 5855.0, 6416.0, 6326.0, 6168.0, 6510.0, 5875.0, 6606.0, 5993.0, 6121.0, 5832.0, 6315.0, 5766.0, 5927.0, 6573.0, 6092.0, 5875.0, 6064.0, 6360.0, 5731.0, 5796.0, 6128.0, 5794.0, 6186.0, 6040.0, 5887.0, 5936.0, 6286.0, 6104.0, 6703.0, 5970.0, 5852.0, 6573.0, 5898.0, 5996.0, 6595.0, 6288.0, 6486.0, 6307.0, 5788.0, 6390.0, 6049.0, 5927.0, 6384.0, 5796.0, 6049.0, 6147.0, 6580.0, 6606.0, 5865.0, 5958.0, 6446.0, 6053.0, 6113.0, 6405.0, 6577.0, 6588.0, 6418.0, 6393.0, 6473.0, 5946.0, 6049.0, 6315.0, 5980.0, 6236.0, 6127.0, 5875.0, 6682.0, 5853.0, 6077.0, 5741.0, 6285.0, 6185.0, 6062.0, 6066.0, 5739.0, 6390.0, 5986.0, 6083.0, 6380.0, 5861.0, 6582.0, 6328.0, 6655.0, 6589.0, 6599.0, 6049.0, 6285.0, 6476.0, 6639.0, 5755.0, 5814.0, 5927.0, 6344.0, 6092.0, 6599.0, 6359.0, 5912.0, 6072.0, 5794.0, 5798.0, 5850.0, 6067.0, 6404.0, 6672.0, 6308.0, 6076.0, 5966.0, 6291.0, 6072.0, 5908.0, 6104.0, 6347.0, 6557.0, 6045.0, 6626.0, 5924.0, 5865.0, 5799.0, 5970.0, 5893.0, 6633.0, 6274.0, 6540.0, 6634.0, 6557.0, 6545.0, 5871.0, 5801.0, 5795.0, 6557.0, 5874.0, 5895.0, 5863.0, 6045.0, 6140.0, 6649.0, 6328.0, 6462.0, 6703.0, 6246.0, 5936.0, 5860.0, 5902.0, 5827.0, 6672.0, 6173.0, 6692.0, 6390.0, 5780.0, 5721.0, 6130.0, 6572.0, 5844.0, 5939.0, 6635.0, 5770.0, 6089.0, 5820.0, 6254.0, 5964.0, 6062.0, 5860.0, 5832.0, 5844.0, 6583.0, 6115.0, 6042.0, 6308.0, 6143.0, 6134.0, 6279.0, 6254.0, 6685.0, 6250.0, 5939.0, 6469.0, 5890.0, 6469.0, 6287.0, 5977.0, 5780.0, 5970.0, 5981.0, 5858.0, 6416.0, 6456.0, 6360.0, 5999.0, 5770.0, 6462.0, 6549.0, 6040.0, 6582.0, 5906.0, 6578.0, 6155.0, 6718.0, 5970.0, 6679.0, 6040.0, 6618.0, 6384.0, 6007.0, 6357.0, 6010.0, 6463.0, 6130.0, 5975.0, 5964.0, 5961.0, 6582.0, 5795.0, 6049.0, 6118.0, 6312.0, 6326.0, 6510.0, 6440.0, 6049.0, 5980.0, 6067.0, 6398.0, 6625.0, 6008.0, 6325.0, 6439.0, 5895.0, 5890.0, 5893.0, 6262.0, 6182.0, 5980.0, 6279.0, 5923.0, 6067.0, 5865.0, 5986.0, 6115.0, 6533.0, 6097.0, 5865.0, 6182.0, 5838.0, 6542.0, 6313.0, 6505.0, 6183.0, 6097.0, 6056.0, 6014.0, 6100.0, 5890.0, 5909.0, 6435.0, 6078.0, 5741.0, 6711.0, 5755.0, 6455.0, 6693.0, 6064.0, 6147.0, 5724.0, 5946.0, 6473.0, 6053.0, 6199.0, 6450.0, 6525.0, 6505.0, 6097.0, 6549.0, 6506.0, 6157.0, 6575.0, 6157.0, 5744.0, 5770.0, 6613.0, 6456.0, 5907.0, 6155.0, 5767.0, 5861.0, 6423.0, 5741.0, 6232.0, 6711.0, 6003.0, 6569.0, 5829.0, 6315.0, 6348.0, 6463.0, 6269.0, 6199.0, 6311.0, 5790.0, 6097.0, 5859.0, 6396.0, 6676.0, 6418.0, 5907.0, 6092.0, 6275.0, 6619.0, 6430.0, 6374.0, 6705.0, 5967.0, 5832.0, 6069.0, 6324.0, 6678.0, 5944.0, 6033.0, 6447.0, 6389.0, 6396.0, 6311.0, 6604.0, 6393.0, 6542.0, 6076.0, 6308.0, 6014.0, 5794.0, 5788.0, 5792.0, 5964.0, 6435.0, 5979.0, 6404.0, 6316.0, 6113.0, 5895.0, 6077.0, 6401.0, 5756.0, 6254.0, 5999.0, 6685.0, 6446.0, 5946.0, 6549.0, 5828.0, 6550.0, 5877.0, 5858.0, 6048.0, 6082.0, 5970.0, 6705.0, 6216.0, 5760.0, 6416.0, 5905.0, 5832.0, 6016.0, 6128.0, 6646.0, 5741.0, 6396.0, 6242.0, 6312.0, 6262.0, 5766.0, 5877.0, 6119.0, 6397.0, 5867.0, 6646.0, 6672.0, 6342.0, 6658.0, 6557.0, 6403.0, 5744.0, 5877.0, 6127.0, 6130.0, 5871.0, 5754.0, 5811.0, 5853.0, 6430.0, 6231.0, 6332.0, 6527.0, 6127.0, 6328.0, 6540.0, 6020.0, 6129.0, 6416.0, 6089.0, 5871.0, 5861.0, 6462.0, 5851.0, 5937.0, 5914.0, 6283.0, 6253.0, 6014.0, 5965.0, 5905.0, 5949.0, 6655.0, 6619.0, 5853.0, 6353.0, 5738.0, 5755.0, 6312.0, 6357.0, 6416.0, 6439.0, 6129.0, 6635.0, 5844.0, 6236.0, 6301.0, 6197.0, 6012.0, 5982.0, 6439.0, 6542.0, 6653.0, 6083.0, 6470.0, 6387.0, 6089.0, 5861.0, 5919.0, 6113.0, 6573.0, 6407.0, 5959.0, 6307.0, 6579.0, 6439.0, 5940.0, 6542.0, 6056.0, 6159.0, 6606.0, 6158.0, 6705.0, 6171.0, 6192.0, 5946.0, 6298.0, 5919.0, 6259.0, 6113.0, 6127.0, 5767.0, 5858.0, 6566.0, 5965.0, 6357.0, 6653.0, 5770.0, 6439.0, 5853.0, 6273.0, 6082.0, 5756.0, 6487.0, 5914.0, 6566.0, 6514.0, 6110.0, 6685.0, 6463.0, 6442.0, 5999.0, 6582.0, 6577.0, 6439.0, 6083.0, 5990.0, 6254.0, 6146.0, 6278.0, 6249.0, 5756.0, 5946.0, 6231.0, 6171.0, 6158.0, 6653.0, 5976.0, 6301.0, 6353.0, 5829.0, 6582.0, 6293.0, 6012.0, 6706.0, 6456.0, 5923.0, 6451.0, 5935.0, 5754.0, 6575.0, 6303.0, 6328.0, 6533.0, 6158.0, 6588.0, 5744.0, 6421.0, 6587.0, 6396.0, 6281.0, 6653.0, 6680.0, 6348.0, 6646.0, 6311.0, 6003.0, 6082.0, 6045.0, 6298.0, 6641.0, 6192.0, 5905.0, 6130.0, 5923.0, 6429.0, 5855.0, 5918.0, 6357.0, 6020.0, 5886.0, 6014.0, 6434.0, 5802.0, 6118.0, 5792.0, 5900.0, 5923.0, 6292.0, 6118.0, 6439.0, 6080.0, 5841.0, 6693.0, 6307.0, 5855.0, 5961.0, 6081.0, 6561.0, 6113.0, 6286.0, 6106.0, 6387.0, 5794.0, 5997.0, 6439.0, 6579.0, 6292.0, 5794.0, 6326.0, 6278.0, 6254.0, 6342.0, 6127.0, 5936.0, 5952.0, 6166.0, 6577.0, 6562.0, 6451.0, 6100.0, 6369.0, 6081.0, 5949.0, 6572.0, 6185.0, 6547.0, 6288.0, 6486.0, 6298.0, 6249.0, 5771.0, 6254.0, 6146.0, 6692.0, 6328.0, 6108.0, 6728.0, 6200.0, 5975.0, 6419.0, 6253.0, 5959.0, 6146.0, 6273.0, 6435.0, 6470.0, 6540.0, 6357.0, 6083.0, 6287.0, 6303.0, 6332.0, 6166.0, 5824.0, 5926.0, 5968.0, 6424.0, 6591.0, 5788.0, 6021.0, 5789.0, 6674.0, 5715.0, 6273.0, 6090.0, 6589.0, 6444.0, 5958.0, 6109.0, 6249.0, 6421.0, 6326.0, 6120.0, 6260.0, 6497.0, 5863.0, 5789.0, 6045.0, 5923.0, 5886.0, 6475.0, 6389.0, 6137.0, 5868.0, 6316.0, 5997.0, 5863.0, 6510.0, 6066.0, 5863.0, 6272.0, 6143.0, 6397.0, 6009.0, 5983.0, 6025.0, 6393.0, 6146.0, 5940.0, 6646.0, 5958.0, 6470.0, 5863.0, 6311.0, 6587.0, 6439.0, 6147.0, 6047.0, 6073.0, 6393.0, 6589.0, 6619.0, 5983.0, 5863.0, 6434.0, 5940.0, 6557.0, 6643.0, 5914.0, 6676.0, 5752.0, 6603.0, 6247.0, 6363.0, 5721.0, 6582.0, 6706.0, 6288.0, 6155.0, 5738.0, 5899.0, 6009.0, 6200.0, 5795.0, 6127.0, 6080.0, 5848.0, 6294.0, 5972.0, 6287.0, 6562.0, 6045.0, 6576.0, 6520.0, 5922.0, 6557.0, 6090.0, 6247.0, 6028.0, 5755.0, 6365.0, 6146.0, 5886.0, 6127.0, 6650.0, 5983.0, 5794.0, 6549.0, 6311.0, 5841.0, 5789.0, 5975.0, 6618.0, 6236.0, 5766.0, 6167.0, 6549.0, 5917.0, 6294.0, 6533.0, 6650.0, 6293.0, 6214.0, 6104.0, 6577.0, 6291.0, 5993.0, 5975.0, 6007.0, 5752.0, 6007.0, 6106.0, 6447.0, 5859.0, 6301.0, 5771.0, 5744.0, 5795.0, 6606.0, 5979.0, 4727.0, 6246.0, 5979.0, 5738.0, 6711.0, 6675.0, 6307.0, 5789.0, 6387.0, 5771.0, 5859.0, 5966.0, 5961.0, 5979.0, 6527.0, 5980.0, 6541.0, 6159.0, 6645.0, 6717.0, 6569.0, 6047.0, 6100.0, 6641.0, 6390.0, 6520.0, 6053.0, 6641.0, 6238.0, 6326.0, 6072.0, 5997.0, 6146.0, 5850.0, 6579.0, 5767.0, 6100.0, 6247.0, 6311.0, 6049.0, 6441.0, 6727.0, 6143.0, 5978.0, 6478.0, 6183.0, 5900.0, 6207.0]
In [290]:
import math
setStartingStationIDs=[value for value in set(starting_station_ids) if not math.isnan(value)]
print setStartingStationIDs
[3074.0, 3075.0, 3076.0, 3077.0, 3078.0, 3079.0, 3080.0, 3081.0, 3082.0, 4108.0, 3056.0, 3000.0, 3005.0, 3006.0, 3007.0, 3008.0, 3009.0, 3010.0, 3011.0, 3014.0, 3016.0, 3018.0, 3019.0, 3020.0, 3021.0, 3022.0, 3023.0, 3024.0, 3025.0, 3026.0, 3027.0, 3028.0, 3029.0, 3030.0, 3031.0, 3032.0, 3033.0, 3034.0, 3035.0, 3036.0, 3037.0, 3038.0, 3039.0, 3040.0, 3042.0, 3045.0, 3046.0, 3047.0, 3048.0, 3049.0, 3051.0, 3052.0, 3053.0, 3054.0, 3055.0, 3057.0, 3058.0, 3059.0, 3060.0, 3062.0, 3063.0, 3064.0, 3065.0, 3066.0, 3067.0, 3068.0, 3069.0]
In [231]:
sortedStartingStationIDs=sorted(setStartingStationIDs, key=float, reverse=True)
sortedEndingStationIDs=sorted(setEndingStationIDs, key=float, reverse=True)
print sortedStartingStationIDs

    
[4108.0, 3082.0, 3081.0, 3080.0, 3079.0, 3078.0, 3077.0, 3076.0, 3075.0, 3074.0, 3069.0, 3068.0, 3067.0, 3066.0, 3065.0, 3064.0, 3063.0, 3062.0, 3060.0, 3059.0, 3058.0, 3057.0, 3056.0, 3055.0, 3054.0, 3053.0, 3052.0, 3051.0, 3049.0, 3048.0, 3047.0, 3046.0, 3045.0, 3042.0, 3040.0, 3039.0, 3038.0, 3037.0, 3036.0, 3035.0, 3034.0, 3033.0, 3032.0, 3031.0, 3030.0, 3029.0, 3028.0, 3027.0, 3026.0, 3025.0, 3024.0, 3023.0, 3022.0, 3021.0, 3020.0, 3019.0, 3018.0, 3016.0, 3014.0, 3011.0, 3010.0, 3009.0, 3008.0, 3007.0, 3006.0, 3005.0, 3000.0]
In [232]:
diffs=[]
for row in sortedStartingStationIDs:
    diff=ending_station_ids.count(row)-starting_station_ids.count(row)
    diffs.append(diff)
print diffs
    
[47, 795, 51, -13, 24, 4, 9, 57, 151, 20, -66, -2269, -316, -222, 24, -56, 814, -121, 6, -20, 136, 19, 20, -810, -25, -1, -756, -123, -665, 151, -236, -214, 132, 1278, -286, 0, -112, 253, 271, 107, -5, 69, 312, 888, -835, -503, -658, -696, -350, 87, -886, 515, 444, 236, 76, 265, 191, -47, 814, 234, -15, 12, 86, -792, 118, 1379, 926]
In [291]:
dict2=zip(sortedStartingStationIDs, diffs)
print dict2
[(4108.0, 47), (3082.0, 795), (3081.0, 51), (3080.0, -13), (3079.0, 24), (3078.0, 4), (3077.0, 9), (3076.0, 57), (3075.0, 151), (3074.0, 20), (3069.0, -66), (3068.0, -2269), (3067.0, -316), (3066.0, -222), (3065.0, 24), (3064.0, -56), (3063.0, 814), (3062.0, -121), (3060.0, 6), (3059.0, -20), (3058.0, 136), (3057.0, 19), (3056.0, 20), (3055.0, -810), (3054.0, -25), (3053.0, -1), (3052.0, -756), (3051.0, -123), (3049.0, -665), (3048.0, 151), (3047.0, -236), (3046.0, -214), (3045.0, 132), (3042.0, 1278), (3040.0, -286), (3039.0, 0), (3038.0, -112), (3037.0, 253), (3036.0, 271), (3035.0, 107), (3034.0, -5), (3033.0, 69), (3032.0, 312), (3031.0, 888), (3030.0, -835), (3029.0, -503), (3028.0, -658), (3027.0, -696), (3026.0, -350), (3025.0, 87), (3024.0, -886), (3023.0, 515), (3022.0, 444), (3021.0, 236), (3020.0, 76), (3019.0, 265), (3018.0, 191), (3016.0, -47), (3014.0, 814), (3011.0, 234), (3010.0, -15), (3009.0, 12), (3008.0, 86), (3007.0, -792), (3006.0, 118), (3005.0, 1379), (3000.0, 926)]

Above shows the net change of bikes per station over the course of the entire time period. Bikes should be transported to stations with the highest negative numbers (or decreases in bikes). So, those would be stations like station 3068.0, which lost 2269 bikes over the time period.